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Recent Submissions
INVESTIGATION OF NITROGEN STATUS IN NOVA SCOTIA VINEYARDS UTILIZING CONVENIENT AND EFFECTIVE TOOLS
(2024-11-27) Bangwei, Zhang; Not Applicable; Doctor of Philosophy; Department of Plant, Food and Environmental Sciences; Not Applicable; Cornelis (Kees) van Leeuwen; Not Applicable; Andrew M. Hammermeister; Gordon W. Price; Keith D. Fuller; David L. Burton
Effective nitrogen management is crucial for vineyards, yet systematic knowledge of vineyard soil nitrogen status is lacking. This project systematically investigated the N status of Nova Scotia vineyards, including N supply, dynamics, and budgets. We validated the effectiveness of biological N availability and N exposure as tools for predicting and monitoring soil N supply. Our research examined soil N status, the responses of soil and vine N to site effects, slope positions, and varying N application rates. Findings showed that N in the sand-sized fraction significantly stabilizes the organic N pool, while N in the micro-fraction is closely associated with the labile N pool. We discovered that site variations affect GSN and SMN retention through differences in organic matter accumulation. Additionally, N fertilizer applications significantly increased N supply post-application, boosting vine growth without notably affecting berry yield or quality.
QUANTIFYING AND COMPARING UNCERTAINTIES WITH BAYESIAN METHODS FOR CLASSIFICATION OF SEAFLOOR IMAGES
(2024-11-25) Voleti, Ritvik; Not Applicable; Master of Computer Science; Faculty of Computer Science; Not Applicable; n/a; Not Applicable; Craig Brown; Janarthanan Rajendran; Thomas Trappenberg
Our oceans are rapidly changing, and mapping the ocean floor is an important task for managing our resources. While vast amounts of seafloor (benthic) image data are available, annotating this data manually remains a significant challenge, even for expert oceanographers. The time and cost required to annotate millions of images are considerable, and additional complications arise from issues such as visibility, orientation, and image quality.
To address these challenges and assist oceanographers in constructing more accurate ocean floor maps, Machine Learning (ML) techniques are employed to automate the classification of benthic images. This study utilizes the BenthicNet dataset, which comprises over 11 million seafloor images. Various ML techniques are applied, including point estimate methods for class memberships, Bayesian Neural Networks (BNNs), and Monte Carlo dropout inference.
The primary focus of this thesis is the evaluation of model uncertainty in the classification of ocean data images using these techniques. Experiments were conducted to assess the reliability and robustness of the models.
Creating a Foundation: First-Year Student Asssessment in Skills-Based Courses
(Centre for Learning and Teaching, 2005-09-01) Le-May Sheffield, Suzanne
In this article the author interviews a handful of different instructors from different programs who implemented skills based courses into their programs during these interviews they discuss the importance of skills based courses as it relates to transitioning students from high school to university as well as diving deeper into what goes into making a skills based course.
How the Source of the Advertisement Influences Susceptibility to Greenwashing: The Roles of the Type of Ad, Perceived Ad Authenticity, and Environmental Concern
(2024-11-26) Goulart Natali, Nicole; Not Applicable; Master of Science; Rowe School of Business; Not Applicable; n/a; Not Applicable; Sergio Carvalho; Christopher Bennett; Hamed Aghakhani; Peggy Cunningham
Companies are increasingly making eco-friendly claims, some of which mislead consumers about their true environmental impact: a phenomenon named greenwashing. This research investigates how the source of an advertisement—shared by a firm or its employees—affects consumer susceptibility to greenwashing. In an experiment, participants viewed an advertisement featuring either a genuine or greenwashing claim shared by one of these sources. The findings reveal that while the source alone does not influence susceptibility, greenwashing advertisements shared by employees are perceived as more authentic, increasing consumer vulnerability. In contrast, consumer evaluations of genuine advertisements remained consistent across sources, while responses to greenwashing claims varied. Environmental concern did not moderate these effects, indicating that even environmentally conscious consumers may fall victim to misleading claims. These results emphasize the need for stricter green marketing standards to address the role of ad sources in amplifying the impact of deceptive environmental messaging.
HYDROGEN BLENDING IN NATURAL GAS PIPELINES: STEEL INTEGRITY AND HYDROGEN EMBRITTLEMENT RISKS
(2024-11-25) Ghadiani, Hesamedin; Not Applicable; Master of Applied Science; Department of Mechanical Engineering; Not Applicable; N/A; Not Applicable; Dr. Kyle Tousignant; Dr. Md. Aminul Islam; Dr. Zoheir Farhat
The depletion of fossil fuel reserves, coupled with the environmental challenges of their combustion, primarily the acceleration of global warming, has shifted focus toward alternative energy sources. Hydrogen gas is a particularly promising option, as it burns cleanly without producing carbon dioxide and is widely recognized as a green energy carrier. Given the extensive infrastructure already in place for natural gas (NG) transportation, repurposing this network for transporting an NG-hydrogen blend could contribute significantly to achieving a carbon-neutral economy. Hydrogen-natural gas blending has gained considerable attention in recent years. However, a major challenge in this approach is the risk of hydrogen embrittlement (HE), a process where hydrogen atoms infiltrate the metal lattice, weakening the material's mechanical properties and potentially causing sudden, severe failures under stress. To assess the feasibility of hydrogen blending within the current NG distribution network, a thorough analysis of pipeline steels is crucial.
Rethinking and Rethinking: Assesment in First Year Law School
(Centre for Learning and Teaching, 2005-09-01) Coughlan, Steve