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Sustainable hazardous waste management: a two-stage dynamic multi-period decision framework
No full textThis thesis presents a comprehensive two-stage dynamic multi-period decision
framework for sustainable hazardous waste management. The first stage involves
optimizing the location and allocation of waste treatment facilities with a focus on
minimizing both cost and emission. The second stage contains a dynamic multi-period
vehicle routing problem (DMPVRP), which allows for real-time adjustments based
on variable pickup dates to cope with dynamics, such that cost, risk, and emission
are simultaneously minimized. Trade-ofs between these objectives are managed by
assigning weight to each objective in both stages. A case study of the healthcare waste
management network in Shanghai, China, demonstrates the model’s applicability
and efectiveness. Results indicate that the proposed system signifcantly improves
cost efciency, reduces environmental impact, and minimizes risk to human health
compared to the current system. Sensitivity analyses further validate the robustness
of the proposed framework, showing improvements across all aspects. This research
provides valuable insights for policymakers and waste management authorities aiming
to enhance the sustainability and resilience of hazardous waste management systems.Includes bibliographical references (pages 64-72
Enhancing Employee Retention in the Healthcare Sector: Evidenced based strategies from the literature and the usage of a psychological debriefing session intervention
No full textEmployee retention is a critical issue for global healthcare organizations, especially given increasing turnover and declining job satisfaction. This two-part thesis explores strategies for enhancing employee retention within the healthcare sector. In part one I present a comprehensive retention plan informed by scholarly literature, emphasizing strategies such as organizational culture change, employee engagement, and professional development. In part two I investigate the potential of a psychological debriefing session on improving perceived organizational support and self-efficacy while reducing burnout and intention to leave among medical laboratory professionals. Using a one-group pretest-posttest design, I used variables such as workload, burnout, and self-efficacy. Although a small sample size limits the ability to draw definitive conclusions, the study contributes to the literature by applying the Job Demands-Resources (JD-R) model and underscores the importance of targeted interventions to address workload-related stressors and improve retention.Includes bibliographical references (pages 80-109
Wta'tukwaqanm - herstory
No full textIn Wta'tukwaqanm², meaning her story, I explore the tension between Western, Eurocentric education systems and Indigenous pedagogy through Indigenous autoethnography. Privileging the role of storytelling as a means of intergenerational knowledge transmission, Wta'tukwaqanm presents a collection of reflective writing that weaves through a circle of seven interconnected elements of learning—spirituality, identity, land, people, language, story, and relationships. Each element draws inspiration from the “Mi’kmaq Creation Story³,” told by Mi’kmaw Elder Stephen Augustine, as it is interpreted and retold through the perspective of Crow. Crow flies into the data presented within the seven chapters of this thesis and helps me to decolonize my thinking by drawing connections between Mi’kmaw values held in the seven levels of creation and the fundamental elements of learning.
In response to the dominant discourse of Western, Eurocentric education, the seven chapters presented in Wta'tukwaqanm provide a model of learning that, while tied to the core of my own identity, can also support the non-assimilative coexistence of differing worldviews. Learning framed in the interconnected aspects of self, and what it means to be human in relation to all of creation, offers an alternative model of learning rooted in relationships and responsibilities.Includes bibliographical references (pages 119-131
The scattering of high frequency electromagnetic radiation from deterministic targets on the ocean surface
No full textAn analysis of the electromagnetic scattering from deterministic targets embedded
in time-varying random rough surfaces is presented. The approach combines and
extends previous works addressing high frequency (HF) electromagnetic scattering
from the ocean and stationary surface targets separately. The analysis begins with
first- and second-order expressions for the normal component of the scattered electric
field from a conducting surface that is small in height and slope and described by a
time-varying Fourier series. A vertical pulsed-dipole transmitting source is assumed
while the observation point of the scattered field remains general. These expressions
are modified to introduce a finite, deterministic target with arbitrary motion via a
Fourier transform of the surface target’s profile. The Fourier integrals in the resulting
expressions are evaluated through asymptotic methods.
The analysis produces two bistatic scattered field expressions involving the surface
target. These are attributed to (1) first- and second-order scatters solely from the
target and (2) a double scatter involving the target and nearby surrounding ocean.
The two components are added to existing expressions for the first- and second-order
scattered fields from the ocean surface to model the total scattered field from an ocean
patch containing a surface target. It is shown that the HF Doppler cross section of
the ocean patch and target may be found as the sum of the cross sections obtained in
treating each field component independently. The target-only and target-ocean cross
sections are formally evaluated, while the ocean-only components are obtained from
existing models. The target-only component is shown to agree with existing monostatic,
zero-velocity results when appropriate substitutions are made. The target-ocean
ii
cross section represents a new expression not seen in previous work, but its general
form is seen to agree with existing bistatic ocean cross section models. Both cross
section components involving target scatter contain a motion-related Fourier factor
similar to one that arises in ocean cross section models for a radar installed on a
floating platform.
The HF Doppler cross sections are simplified for the case of a surface target moving
with constant velocity. It is shown that the target-only cross section contains
a Dirac delta function with an argument restricting the response to an impulse at
the bistatic Doppler frequency shift predicted for uniform linear motion. The oceantarget
component also contains a Dirac delta function with an argument containing
the constant-velocity bistatic Doppler shift in addition to terms related to ocean dispersion
and the change in target location between radar acquisitions. A system model
of an HF radar suitable for predicting the received Doppler power spectral density
from an ocean patch containing a surface target is presented. The system model is
used to predict the received signal strength for a variety of target, environmental,
and radar operating parameters. The results of the computations show, that under
certain conditions, a constant velocity target whose first-order cross section is masked
by ocean clutter may be detected through a secondary scatter from the ocean surface.
The models derived in this work enable the establishment of suitable design specifications
and operating parameters when developing new or utilizing existing HF
surface wave radar systems for the purposes of monitoring targets on the ocean surface.
In addition, the physical interpretation of the scattering process and simple
computation provided by the models should prove relevant in developing and testing
novel signal processing techniques for both target identification and clutter rejection.Includes bibliographical references (pages 121-133
Fault reactivation and structural control on sedimentation along the Laurentian passive Margin: The Cambrian to Ordovician Cow Head Group, Humber zone, Western Newfoundland
No full textSedimentologic and provenance analyses were conducted on the upper Cambrian and Lower Ordovician
Cow Head Group in western Newfoundland, Canada, to understand the structural control on sedimentation
of these passive Laurentian margin strata. Four facies associations were identified, corresponding to
submarine slope sub-environments. Facies association 1 (FA1) is characterized by amalgamated sheet-like
architectural elements composed of debris and hyperconcentrated transitional to concentrated flow strata,
comprising sections through the Miaolingian series and across the Cambro-Ordovician boundary. FA1
occurs both below and above Furongian FA2 and its coeval distal FA3, and beneath the Lower Ordovician
FA4. High-energy sedimentary processes such as reflected turbidity currents and/or tsunami-related
oscillatory currents are recorded in Furongian stratigraphy of FA2 by HCS-like stratification, and these
strata are capped by boulder mega-conglomerates at the Cambrian-Ordovician boundary recording shortdistance
rock fall processes related to basin margin collapse (FA1). These strata are overlain by facies
recording calmer depositional conditions in the Early Ordovician, characterized by low-concentration
turbidity currents (FA3). Together, these facies associations record the transition from a platform margin
fault scarp basin (FA1) to a confined submarine basin, including confined slope (FA2) and lower slope to
basin floor (FA3) settings, succeeded by basin margin collapse during the Cambrian-Ordovician transition
(FA1) and an Early Ordovician passive toe of slope sedimentation (FA4). Paleocurrent measurements
indicate a southward-facing submarine paleoslope. U-Pb geochronology and Lu-Hf isotopic analysis of
detrital zircon suggest sediment recycling of earlier deposited Paleozoic shelf units and erosion down to
Ediacaran igneous rift-related rocks on the margin, implying tectonic uplift and transverse fault reactivation
along the Laurentian margin. The regional significance of this late Cambrian to Early Ordovician (495 to
480 Ma) sedimentary succession highlights the structural control on the Laurentian passive margin, and is
consistent with its existing rift-architecture models and links to the geodynamic evolution of the Taconic
Seaway
Constrained CO₂EOR: optimization considering impurities, CO₂EOR type, volume, and oil recovery vs CO₂ storage
No full textOptimizing CO₂ injection in offshore Enhanced Oil Recovery (EOR) operations aims to increase oil production while capturing CO₂, aligning with global carbon capture and storage (CCS) goals. CO₂ dissolves in oil, reducing its viscosity and making it more extractable, but offshore sites face unique challenges, such as limited CO₂ supply, high storage costs, and technical constraints. Various EOR methods can address these limitations: Carbonated Water Injection (CWI) dissolves CO₂ in water, reducing the total CO₂ required and enhancing oil recovery while maximizing carbon retention. Another approach, targeted CO₂ flooding in specific reservoir blocks, concentrates CO₂ where it's most effective, making efficient use of limited supplies. Water-Alternating-Gas (WAG) injection alternates CO₂ and water to manage gas mobility and improve the efficiency of oil displacement, allowing for strategic use of CO₂ without full-field application. This study analyzes the optimization of constrained volumes of varying CO2 concentrations and impurities considering different oil types and reservoir conditions. It examines how impurities impact CO₂ injection and retention, and how different oil types and reservoir characteristics respond to specific injection strategies. This approach enables offshore EOR to balance enhanced oil recovery with carbon storage objectives, optimizing both CO₂ usage efficiency and emission reductions to support sustainable energy goals.
Current carbon capture technologies are imperfect, resulting in impurities within the CO₂ stream that affect the Minimum Miscibility Pressure (MMP) needed for effective oil recovery. This study investigates how these impurities influence the MMP in oil and gas mixtures using slimtube simulations across a range of CO₂ sources and capture technologies. While prior studies often focus on pure or low (<5 %) CO₂ concentrations, this research explores a broader range, examining CO₂ concentrations from 0 % to 100 % to fill an existing gap in the literature. The study reveals that
impurities depend on the CO₂ source: for example, CH₄ is common in CO₂ from natural gas streams, while O₂ and N₂ are prevalent in CO₂ from flue gas. The results indicate that CO₂ mixed with natural gas effectively lowers MMP, enhancing miscibility, whereas impurities in flue gas (like O₂ and N₂) raise the MMP more significantly, as N₂ requires particularly high pressures to reach miscibility compared to CO₂. This work deepens understanding of the impacts of different CO₂ sources and impurity levels on MMP, contributing valuable insights for optimizing CO₂-based enhanced oil recovery processes.
Understanding the Minimum Miscibility Pressure (MMP) between oil and gas mixtures is essential for accurately predicting reservoir performance, particularly in enhanced oil recovery (EOR) processes. However, no single Equation of State (EOS) consistently predicts fluid properties across all conditions. Machine Learning (ML) has become a valuable tool for estimating MMP, yet prior studies have often faced limitations due to small data sets and restricted ranges of CO₂ mole percentages. This study develops a Machine Learning model using Deep Learning and k-fold Cross Validation techniques, improving the size, accuracy, and range of the data, particularly for CO₂ concentrations. Additionally, a sensitivity analysis is performed to assess the influence of various input parameters, such as reservoir characteristics and oil and gas properties, on MMP. The study finds that key factors impacting MMP include reservoir temperature and the concentrations of CO₂ and methane (C₁) in the gas phase. Higher temperatures, heavier oils, a greater proportion of volatile and intermediate components in the oil, and higher concentrations of C₁ and N₂ in the gas phase all lead to higher MMP. In contrast, the presence of CO₂ and H₂S, especially CO₂, significantly lowers the MMP, aiding oil recovery. The study emphasizes how Deep Learning approaches can enhance the accuracy and range of MMP predictions, improving the optimization of EOR strategies by providing better insights into fluid dynamics.
Previous studies in Enhanced Oil Recovery (EOR) and Carbon Capture, Utilization, and Storage (CCUS) have largely operated under the assumption of unlimited CO₂ supply, failing to adequately address the constraints associated with CO₂ availability, especially in offshore reservoirs. This oversight is significant, as the capacity for CO₂ storage and the ability to conduct effective EOR can be severely limited by the volume of CO₂ that can be feasibly captured and injected. Moreover, most EOR research tends to emphasize incremental oil recovery metrics while neglecting the financial impacts of carbon emissions, which can significantly influence project feasibility and sustainability. This study investigates the joint optimization of oil recovery and carbon storage by considering both the economic value of produced oil and the benefits of CO₂ tax credits, assigning equal weight to each factor with a 50:50 ratio. It examines various oil types (light, medium, and heavy) and reservoir conditions, including CO₂-EOR methods such as Water-Alternating-Gas (WAG), Carbonated Water Injection (CWI), and enriched-WAG, under different CO₂ constraints, impurities, and reservoir characteristics like stratification, crossflow, temperature, pressure, and permeability. The simulations use GMG, and optimization is performed using Multi-Objective Particle Swarm Optimization (MOPSO). The results show that CWI is the most effective method under CO₂ constraints for stratified reservoirs, whether crossflow is present or not. However, CO₂ storage is significantly lower in the CWI case. Among the factors influencing optimization, reservoir pressure has the most significant effect on the overall objectives, while permeability is the key factor in determining the oil recovery factor across all three CO₂-EOR methods.
EOR studies typically focus on incremental oil recovery (without considering carbon pricing), whereas Carbon Capture, Utilisation and Storage (CCUS) prioritizes maximizing CO₂ storage (assuming an infinite CO₂ supply). The joint optimization of oil recovery factor and CO₂ storage varies based on phase behavior related to different oil types and conditions (EOR methods, the available amount and characteristics of injected gas, and reservoir properties), but also on economic
factors such as the price of produced oil and the value of CO₂ tax credits. By incorporating all these factors into simulations and applying modern machine learning techniques, we can better optimize the balance between enhancing oil recovery and reducing carbon intensity during the energy transition era. Machine learning models can simulate and predict outcomes for various reservoir conditions and economic scenarios, enabling more informed decisions on the selection of the most appropriate EOR technique, the optimal amount of CO₂ to inject and also the precise conditions under which oil recovery and CO₂ storage can be balanced most effectively for a specific reservoir.Includes bibliographical reference
Why are graduate students' note-taking practices noteworthy?
No full textAlthough note-taking is generally seen as vital to students’ academic success, students are normally left to find their own way in mastering note-taking (Blair, 2004; Coullie, 2020; Lessa et al., 2022), particularly within graduate studies (Fine et al., 2021; Wohl & Fine, 2017b). Most of the literature discussing note-taking centres on undergraduates and classroom listening contexts (Fine et al., 2021). However, there is need to investigate graduate note-taking practices from reading away from the classroom, as assumptions and expectations that all students entering graduate studies are/should be proficient in graduate-level reading is unrealistic (Liu & Pullinger, 2021) and unreasonable (Reid, 2018; Wohl & Fine, 2017b), particularly considering the diverse cultural and linguistic backgrounds typifying graduate student enrolment across North American universities. This textographic study explores and analyzes the note-taking practices of a small sample of graduate students enrolled in an Atlantic Canada university, drawing from Academic Literacies theory, particularly Lillis’ (2008) notions of how people’s “talk around text” index or point to the wider social context and people’s orientation (beliefs/values/attitudes) to their textual practices. While each student developed note-taking strategies that helped them to cope with the large volumes of readings, and the depth of critical reading required, an individual unfamiliar with Western academic writing norms can be at a distinct disadvantage in avoiding charges of plagiarism. While the literature on note-taking privileges generative note-taking strategies, there is greater need for appreciation for how non-generative note-taking strategies are efficacious for some students. In addition, while this study resists seeing students’ note-taking practices in deficit terms, instead presenting the students’ own assessments of their note-taking practices, a case is being made for further developing students’ reading proficiencies through explicit instruction in note-taking
Augmentation of onboard camera data with vessel manoeuvrability for tactical navigational support analysis
No full textShipping in Canadian Arctic waters involves significant risks, primarily due to potential ice interactions. To address these challenges, various support tools have been developed to enhance safe navigation in ice-prone regions. These include POLARIS, a system which evaluates vessel suitability for specific ice conditions, and onboard cameras, which act as sensors to capture and monitor ice conditions around a vessel. This study examines the effectiveness of these two decision support tools, emphasizing the need to account for operational parameters such as vessel speed and physical characteristics like vessel length when assessing a ship's ability to navigate safely through ice.
Image processing techniques, including projective transformation, are applied to convert onboard camera data into a top-down view, enabling augmentation of ship manoeuvrability parameters stopping distance and turning circle. Image rescaling is further employed to achieve a true-scale representation of distances within the field of view. Two sample vessels are analyzed to evaluate their manoeuvrability in a test case involving a 50m diameter ice hazard at 175m directly ahead of the vessel. The results demonstrate the critical role of vessel speed in stopping distance and vessel length in the turning circle. The results also show the limitations of using onboard cameras for tactical navigational support, as well as highlighting the limits that POLARIS has in terms of accounting for differences in vessels within the same ice class but with different capabilities.Includes bibliographical references (pages 77-86
Comparing different brain computer interface control tasks, across multiple online sessions
No full textMotor imagery (MI)-based brain-computer interfaces (BCIs) offer a promising avenue
for enabling communication and control in individuals with motor impairments.
While prior studies have largely focused on decoding short, discrete MI trials, the feasibility
of decoding MI tasks continuously over longer intervals - as would be needed in
applications like wheelchair, drone, or avatar control - is less understood. This study
examined the online classification of four MI tasks (Hand, Feet, Tongue, Singing)
versus rest using EEG in such a simulated continuous control paradigm.
Ten healthy participants engaged in trials of alternating intervals of MI tasks and
rest, with intervals ranging from 8 to 20 seconds, over three sessions. A real-time
decoding pipeline was implemented using overlapping 4-second epochs, filter bank
common spatial patterns (FBCSP), mRMR feature selection, and linear discriminant
analysis (LDA) classification. Mean accuracies exceeded the statistical threshold for
chance performance (53.3%) for all MI tasks, with average performance ranging from
66.7% to 71.6%. Notably, decoding accuracy improved significantly from Session 1 to
Session 2, though gains plateaued with no further improvement in Session 3.
Inter-participant variability was evident: eight out of ten participants surpassed
the 70% accuracy threshold often cited as being necessary for practical BCI use in at
least one task, while two participants consistently performed near or below threshold,
aligning with prior observations of BCI illiteracy. Despite Tongue MI being rated as
the most difficult task overall, it yielded the highest average decoding accuracy and
was the best-performing task for half of the participants. Participant ratings also
revealed Hand MI as the most preferred task and Singing as the least favored.
These findings demonstrate the viability of continuous MI decoding with real-time
feedback and highlight the influence of individual differences and user experience.
Further research is needed to assess performance in multi-task scenarios, across longer training periods, using alternate feedback strategies, and in real-world environments
with the target population of BCI users
Fleas on the run: a re-examination of pulex irritans biogeography through an interdisciplinary framework
No full textThe Human Flea (Pulex irritans) is a cosmopolitan ectoparasite associated with humans since at least 5,000 years. Originating in South America, the Human Flea achieved global distribution through mechanisms tied to human activity, yet many aspects of its biogeography remain poorly understood. This thesis addresses key questions about this flea’s origins and dispersal by integrating modern, historical, and fossil records. Building on Buckland and Sadler’s (1989) seminal study, this research re-evaluates their hypotheses in light of new archaeological data and interdisciplinary evidence. I employ a structured interdisciplinary framework to consolidate diverse datasets and uncover patterns and gaps in the Human Flea’s biogeography. Findings in this thesis reveal the complex role of human activity—through migration, trade, and environmental modifications—in shaping the Human Flea’s global spread and subsequent decline. This research contributes to the field of biodiversity, demonstrating the value of cross-disciplinary approaches in biogeography. Furthermore, I offer a framework for integrating diverse data sources to advance understanding of species distribution and their relationships with human hosts