Trent University Graduate Thesis Collection

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    Copyright for all items in the Trent University Graduate Thesis Collection is held by the author, with all rights reserved, unless otherwise noted.
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    Modelling Depressive Symptoms in Emerging Adulthood: Intergenerational Risk and the Protective Role of Trait Emotional Intelligence

    Year: 2020, 2020
    Member of: Trent University Graduate Thesis Collection
    Name(s): Creator (cre): Snetsinger, Samantha Wynne, Thesis advisor (ths): Parker, James, Degree committee member (dgc): Keefer, Kateryna, Degree committee member (dgc): Carter, Bruce, Degree granting institution (dgg): Trent University
    Abstract: <p>Depression during the transition into adulthood is a growing mental health concern, with overwhelming evidence linking the developmental risk for depressive symptoms with maternal depression. In addition, there is a lack of research on the protective role of socioemotional competencies in this context. This study examines independent and joint effects of maternal depression and trait… more

    Characteristics of Models for Representation of Mathematical Structure in Typesetting Applications and the Cognition of Digitally Transcribing Mathematics

    Year: 2020, 2020
    Member of: Trent University Graduate Thesis Collection
    Name(s): Creator (cre): Quinby, Francis, Thesis advisor (ths): Burr, Wesley S., Thesis advisor (ths): Pollanen, Marco, Degree committee member (dgc): Reynolds, Michael G., Degree granting institution (dgg): Trent University
    Abstract: <p>The digital typesetting of mathematics can present many challenges to users, especially those of novice to intermediate experience levels. Through a series of experiments, we show that two models used to represent mathematical structure in these typesetting applications, the 1-dimensional structure based model and the 2-dimensional freeform model, cause interference with users'… more

    Time Series Algorithms in Machine Learning - A Graph Approach to Multivariate Forecasting

    Year: 2020, 2020
    Member of: Trent University Graduate Thesis Collection
    Name(s): Creator (cre): Zhou, Ryan, Thesis advisor (ths): Feng, Wenying, Degree committee member (dgc): Alam, Omar, Degree granting institution (dgg): Trent University
    Abstract: <p>Forecasting future values of time series has long been a field with many and varied applications, from climate and weather forecasting to stock prediction and economic planning to the control of industrial processes. Many of these problems involve not only a single time series but many simultaneous series which may influence each other. This thesis provides methods based on machine… more

    Representation Learning with Restorative Autoencoders for Transfer Learning

    Year: 2020, 2020
    Member of: Trent University Graduate Thesis Collection
    Name(s): Creator (cre): Fichuk, Dexter Lamont, Thesis advisor (ths): McConnell, Sabine, Degree committee member (dgc): Hurley, Richard, Degree granting institution (dgg): Trent University
    Abstract: <p>Deep Neural Networks (DNNs) have reached human-level performance in numerous tasks in the domain of computer vision. DNNs are efficient for both classification and the more complex task of image segmentation. These networks are typically trained on thousands of images, which are often hand-labelled by domain experts. This bottleneck creates a promising research area: training accurate… more

    A Framework for Testing Time Series Interpolators

    Year: 2020, 2020
    Member of: Trent University Graduate Thesis Collection
    Name(s): Creator (cre): Castel, Sophie Terra Marguerite, Thesis advisor (ths): Burr, Wesley S, Degree committee member (dgc): Pollanen, Marco, Degree granting institution (dgg): Trent University
    Abstract: <p>The spectrum of a given time series is a characteristic function describing its frequency properties. Spectrum estimation methods require time series data to be contiguous in order for robust estimators to retain their performance. This poses a fundamental challenge, especially when considering real-world scientific data that is often plagued by missing values, and/or irregularly… more

    Problem Solving as a Path to Understanding Mathematics Representations: An Eye-Tracking Study

    Year: 2020, 2020
    Member of: Trent University Graduate Thesis Collection
    Name(s): Creator (cre): Kim, Seyeon, Thesis advisor (ths): Burr, Wesley, Thesis advisor (ths): Pollanen, Marco, Degree committee member (dgc): Chan-Reynolds, Michael, Degree granting institution (dgg): Trent University
    Abstract: <p>Little is actually known about how people cognitively process and integrate information when solving complex mathematical problems. In this thesis, eye-tracking was used to examine how people read and integrate information from mathematical symbols and complex formula, with eye fixations being used as a measure of their current focus of attention. Each participant in the studies was… more

    Development of a Cross-Platform Solution for Calculating Certified Emission Reduction Credits in Forestry Projects under the Kyoto Protocol of the UNFCCC

    Year: 2020, 2020
    Member of: Trent University Graduate Thesis Collection
    Name(s): Creator (cre): McIntyre, Gregory, Thesis advisor (ths): Ponce-Hernandez, Raul, Thesis advisor (ths): Hurley, Richard, Degree committee member (dgc): Hircock, Brian, Degree granting institution (dgg): Trent University
    Abstract: <p>This thesis presents an exploration of the requirements for and development of a software tool to calculate Certified Emission Reduction (CERs) credits for afforestation and reforestation projects conducted under the Clean Development Mechanism (CDM). We examine the relevant methodologies and tools to determine what is required to create a software package that can support a wide variety… more

    Sinc-Collocation Difference Methods for Solving the Gross-Pitaevskii Equation

    Year: 2020, 2020
    Member of: Trent University Graduate Thesis Collection
    Name(s): Creator (cre): Kang, Shengnan, Thesis advisor (ths): Abdella, Kenzu, Thesis advisor (ths): Pollanen, Marco, Degree granting institution (dgg): Trent University
    Abstract: <p>The time-dependent Gross-Pitaevskii Equation, describing the movement of parti-</p><p>cles in quantum mechanics, may not be solved analytically due to its inherent non-</p><p>linearity. Hence numerical methods are of importance to approximate the solution.</p><p>This study develops a discrete scheme in time and space to simulate the solution</p>… more

    Pathways to Innovation: Modelling University-to-Firm Research Development

    Year: 2020, 2020
    Member of: Trent University Graduate Thesis Collection
    Name(s): Creator (cre): Hamani, Sanaa, Thesis advisor (ths): Cater, Bruce, Thesis advisor (ths): Pollanen, Marco, Degree granting institution (dgg): Trent University
    Abstract: <p>Research and development activities conducted at universities and firms fuel economic growth</p><p>and play a key role in the process of innovation. Specifically, prior research has investigated the</p><p>widespread university-to-firm research development path and concluded that universities are</p><p>better suited for early stage of research while… more

    Combinatorial Collisions in Database Matching: With Examples from DNA

    Year: 2020, 2020
    Member of: Trent University Graduate Thesis Collection
    Name(s): Creator (cre): Johnson, Stephanie, Thesis advisor (ths): Pollanen, Marco, Thesis advisor (ths): Burr, Wesley, Degree granting institution (dgg): Trent University
    Abstract: <p>Databases containing information such as location points, web searches and fi- nancial transactions are becoming the new normal as technology advances. Conse- quentially, searches and cross-referencing in big data are becoming a common prob- lem as computing and statistical analysis increasingly allow for the contents of such databases to be analyzed and dredged for data. Searches… more

    Automated Grading of UML Class Diagrams

    Year: 2020, 2020
    Member of: Trent University Graduate Thesis Collection
    Name(s): Creator (cre): Bian, Weiyi, Thesis advisor (ths): Alam, Omar, Degree committee member (dgc): Feng, Wenying, Degree committee member (dgc): Gherbi, Abdelouahed, Degree granting institution (dgg): Trent University
    Abstract: <p>Learning how to model the structural properties of a problem domain or an object-oriented design in form of a class diagram is an essential learning task in many software engineering courses. Since grading UML assignments is a cumbersome and time-consuming task, there is a need for an automated grading approach that can assist the instructors by speeding up the grading process, as well… more

    Solving Differential and Integro-Differential Boundary Value Problems using a Numerical Sinc-Collocation Method Based on Derivative Interpolation

    Year: 2020, 2020
    Member of: Trent University Graduate Thesis Collection
    Name(s): Creator (cre): Ross, Glen Charles, Thesis advisor (ths): Abdella, Kenzu, Degree committee member (dgc): Pollanen, Marco, Degree granting institution (dgg): Trent University
    Abstract: <p>In this thesis, a new sinc-collocation method based upon derivative interpolation is developed for solving linear and nonlinear boundary value problems involving differential as well as integro-differential equations. The sinc-collocation method is chosen for its ease of implementation, exponential convergence of error, and ability to handle to singularities in the BVP. We present a… more

    Fraud Detection in Financial Businesses Using Data Mining Approaches

    Year: 2020, 2020
    Member of: Trent University Graduate Thesis Collection
    Name(s): Creator (cre): Moudarres, Anissa Nour, Thesis advisor (ths): McConnell, Sabine, Thesis advisor (ths): Hurley, Richard, Degree granting institution (dgg): Trent University
    Abstract: <p>The purpose of this research is to apply four methods on two data sets, a Synthetic</p><p>dataset and a Real-World dataset, and compare the results to each other with the</p><p>intention of arriving at methods to prevent fraud. Methods used include Logistic Regression,</p><p>Isolation Forest, Ensemble Method and Generative Adversarial Networks.</p… more