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Machine learning techniques for self-interference cancellation in full-duplex systems
No full textFull-duplex (FD), enabling remote parties to transfer information simultaneously in
both directions and in the same bandwidth, has been envisioned as an important
technology for the next-generation wireless networks. This is due to the ability to
leverage both time and frequency resources and theoretically double the spectral efficiency. Enabling the FD communications is, however, highly challenging due to the
self-interference (SI), a leakage signal from the FD transmitter (Tx) to its own receiver
(Rx). The power of the SI is significantly higher when compared with the signal of
interest (SoI) from a remote node due to the proximity of the Tx to its co-located Rx.
The SI signal is thus swamping the SoI and degrading the FD system's performance.
Traditional self-interference cancellation (SIC) approaches, spanning the propagation,
analog, and/or digital domains, have been explored to cancel the SI in FD
transceivers. Particularly, digital domain cancellation is typically performed using
model-driven approaches, which have proven to be effective for SIC; however, they
could impose additional cost, hardware, memory, and/or computational requirements.
Motivated by the aforementioned, this thesis aims to apply data-driven machine
learning (ML)-assisted SIC approaches to cancel the SI in FD transceivers|in the digital
domain|and address the extra requirements imposed by the traditional methods.
Specifically, in Chapter 2, two grid-based neural network (NN) structures, referred
to as ladder-wise grid structure and moving-window grid structure, are proposed to
model the SI in FD transceivers with lower memory and computational requirements
than the literature benchmarks. Further reduction in the computational complexity
is provided in Chapter 3, where two hybrid-layers NN structures, referred to as
hybrid-convolutional recurrent NN and hybrid-convolutional recurrent dense NN, are
proposed to model the FD SI. The proposed hybrid NN structures exhibit lower computational
requirements than the grid-based structures and without degradation in the
SIC performance. In Chapter 4, an output-feedback NN structure, referred to as the
dual neurons-` hidden layers NN, is designed to model the SI in FD transceivers with
less memory and computational requirements than the grid-based and hybrid-layers
NN structures and without any additional deterioration to the SIC performance.
In Chapter 5, support vector regressors (SVRs), variants of support vector machines,
are proposed to cancel the SI in FD transceivers. A case study to assess the
performance of SVR-based approaches compared to the classical and other ML-based
approaches, using different performance metrics and two different test setups, is also
provided in this chapter. The SVR-based SIC approaches are able to reduce the training
time compared to the NN-based approaches, which are, contrarily, shown to be
more efficient in terms of SIC, especially when high transmit power levels are utilized.
To further enhance the performance/complexity of the ML approaches provided
in Chapter 5, two learning techniques are investigated in Chapters 6 and 7. Specifically,
in Chapter 6, the concept of residual learning is exploited to develop an NN
structure, referred to as residual real-valued time-delay NN, to model the FD SI with
lower computational requirements than the benchmarks of Chapter 5. In Chapter 7,
a fast and accurate learning algorithm, namely extreme learning machine, is proposed
to suppress the SI in FD transceivers with a higher SIC performance and lower training
overhead than the benchmarks of Chapter 5. Finally, in Chapter 8, the thesis
conclusions are provided and the directions for future research are highlighted.Includes bibliographical reference
Elizabeth Grymeston’s Miscelanea, Meditations, Memoratives and the commonplace-book culture of sixteenth-century English women writers
No full textElizabeth Grymeston’s Miscelanea, Meditations, Memoratives (1604) has generally been
considered one of the earliest and most polished examples of late sixteenth- and
seventeenth-century mother’s legacy genre. Written between 1601 and 1603 and published
posthumously in four reprints (1604, 1606?, 1608?, 1618?), Grymeston’s work is routinely
compared to that of seventeenth-century mother’s legacy writers Dorothy Leigh and Elizabeth
Joceline. However, despite being dedicated to Grymeston’s only son, Bernye Grymeston,
Miscelanea is not only a tract of motherly advice but also a survey of Grymeston’s life events,
biblical knowledge, religious loyalties, and reading materials. In fact, as I will argue,
Grymeston’s compilation displays the reading, extracting, and gathering characteristic of early
modern commonplace books and can be compared more effectively to devotional collections
such as Lady Frances Abergavenny’s prayers, published in Thomas Bentley’s anthology The
Monument of Matrones (1582). In this thesis, I reconsider, therefore, Grymeston’s compilation
within the context of the humanist educational practice of commonplacing and compare her work
to the female-authored commonplace books of Katherine Parr and Elizabeth I. By
recontextualizing Grymeston’s Miscelanea and applying a more flexible definition of the
mother’s legacy genre especially in regards to its sixteenth-century representatives, I intend to
redefine Grymeston’s place within the commonplace-book culture of early modern English
women writers.Includes bibliographical references (pages 87-94
The impact of corporate social responsibility on corporate financial performance
No full textThis study analyzes the relationship between corporate social responsibility (CSR) and the corporate financial performance of companies listed on the Toronto Stock Exchange (TSX 60 Companies). Environmental, social, and governance disclosure scores are used to measure CSR based on three dimensions; Environmental (ENV), social (SOC), and governance (GOV) performance. Return on asset (ROA), return on equity (ROE) and earnings per share (EPS) were used to measure corporate financial performance. I used a partial least squares path modelling package in RStudio to analyze the relationship between the dependent and the independent variables for the period 2018–2022. The results revealed that ENV has a significant positive relationship with ROA and SOC has a significant negative relationship with ROA. Whereas ENV has a significant negative relationship with ROE and SOC has a significant positive relationship with ROE. Also, ENV has a significant negative relationship with EPS; no significant relationship was found between SOC and EPS. GOV does not exhibit a significant relationship with ROA, ROE, and EPS. However, I found that the relationship between the three dimensions of CSR and the measure of corporate financial performance is moderated by company size and risk. These findings highlight that various CSR activities impact different aspects of company performance in unique ways. This result can guide managers in prioritizing implementing CSR activities based on their desired financial outcomes.Includes bibliographical references (pages 44-56
Protein politics: Sustainable protein and the logic of energy
No full textPowerful actors associated with intensive livestock production are repositioning industrially produced meat and farmed fish as “sustainable protein.” This repositioning, we show, involves justifying the production of meat through a range of metrics, calculations, and valuations. These metrics and associated indicators underpin claims that sustainable protein is more efficient and less wasteful than conventional meat production. Our analysis questions the relationship between efficiency and sustainability in industrial meat production. We show, first, that the industrial meat sector has always focussed on efficiency and the reduction of waste. What is new is that metrics, calculations, and indicators on efficiency and waste reduction are being repurposed and made public to consumers and investors to underpin claims for sustainable and “climate friendly” meat. While this practice is apparent across the animal agriculture sector, it is especially evident in the production of farmed salmon. Our second argument frames sustainable protein metrics as a political logic. While these metrics have been justifiably criticized as a form of environmental “greenwashing” by environmental non-governmental organizations and others, our own critique builds on Cara Daggett’s recent analysis of energy and its political logic. Building on Daggett’s work, we aim to provide a more fundamental critique to the efficiency and waste metrics that are used to support claims for sustainable protein, while simultaneously providing the conceptual and political foundation for more progressive futures
"What am I doing here?" Imposter syndrome and institutional structures propagating feelings of inadequacy among graduate students
No full textWe have all felt incredibly inadequate at some point in our lives. The pervasive thought that “everybody is more brilliant than me” is more common than we think. However, how often do we think of it as being propagated by institutional factors? My study examines how imposter syndrome, structural constraints, and their meanings interplay in academia. I spoke to 20 graduate students from different faculties, backgrounds, and genders at the Memorial University of Newfoundland (MUN) via semi-structured interviews. I found that participants frequently used impression management techniques, consistently showcasing skills, achievements, or levels of knowledge through their narrations. Participants approached imposter syndrome mainly as an internal personal issue, constantly comparing themselves to other people’s situations. In doing so, they used a single definition of success or failure in academia. However, the data showed that structural factors, such as racism, patriarchy, colonialism, a working yourself-to-the-bone culture, lack of support from gatekeepers, and COVID-19, all had an immense impact on feelings of inadequacy and self-doubt among graduate students.Includes bibliographical references (pages 173-199
Applications of machine learning for modelling of ice flexural strength
No full textThe design of marine vessels and structures operating in regions where ice is present, must
consider the loads transferred to the structure upon impact with an ice feature. The flexural
strength of ice is an important material property and can have significant impact on the
loads transferred to a structure. Flexural strength is generally considered to be dependent
on the size or scale of the sample (often reported as beam volume), ice temperature and
brine volume (in the case of sea ice), however the influence of temperature and beam volume
have been debated in the literature. Conventionally flexural strength was often modelled as
a constant (i.e. average strength), or was modelled as a single parameter or dual parameter
(sea ice only) empirical relationship. Employing an extensive database of flexural strength
measurements, with over 2000 freshwater and 2800 sea ice measurements, machine learning
(ML) algorithms were utilized to define a relationship between these ice parameters and the
measured flexural strength. The implementation of ML algorithms was able to highlight a
link between freshwater flexural strength and ice temperature, a relationship often ignored or
not perceivable in existing models. When considering sea ice, the use of ML algorithms were
able to highlight a dependence of flexural strength on scale, brine volume and temperature.
These findings have the potential to impact the design of ice strengthened structures, and
highlights the importance of accurately recording these parameters when performing tests
in the either the field or laboratory.Includes bibliographical references (pages 146-152
Barriers and enablers to successful hyperacute ischemic stroke care
No full textStroke is a leading cause of adult disability. Thrombolysis, and Endovascular Therapy (EVT) significantly reduce disability of ischemic stroke patients (85% of strokes). However, in Newfoundland and Labrador (NL), thrombolysis rates were low, and EVT only began in 2022. In addition, NL had a higher incidence of stroke, with worse outcomes than the rest of Canada. Due to the availability of data, this study used a mixed methods approach to investigate stroke care processes in the Eastern Health (EH) region of Newfoundland and Labrador (NL) and three other Canadian regions (Central zone Nova Scotia (NS), Southeastern Ontario (SEO) and Calgary zone Alberta) to identify policy recommendations to improve hyperacute stroke care.
First, two time series analyses compared indicators between stroke centres between each region. In addition, case studies in each region were completed to provide a subjective view of their hyperacute ischemic stroke care. Using literal replication, the case studies recorded semi-structured interviews with stroke care professionals. For data triangulation, stroke care documents and archival data were requested. Through thematic analysis, the goal was to understand critical success factors to optimize efficient hyperacute ischemic stroke care. Finally, using cross-case synthesis, regions were compared using matrices to understand how they differ. The Health Science Centre (HSC) in EH showed impressive improvements from 2016/2017 to 2020/2021 with thrombolysis rates rising from 9.6% to 19.0%, nearing their target of 21.0%. In addition, HSC had similar indicators compared to the three Comprehensive Stroke Centres (CSCs) in the other regions. The four Primary Stroke Centres (PSCs) of EH have not shown the same improvement. However, SEO and Calgary reported Belleville and Red Deer as highly functioning PSCs due to their strong stroke champions, nursing leadership, and team culture. As the cases presented similar care models, I have concluded that EH PSC programs must
standardize and map out processes supporting efficient treatment and improve early communication. Passionate leaders are also required to motivate teams and find time for change management and continuous quality improvement. The policy implications of the results suggest ways to improve hyperacute stroke care in NL: 1) Develop a provincial stroke program to standardize stroke care across the province, monitor performance, and collaborate with the air and ground ambulance system, 2) Expand EVT to a full-time service serving eligible patients across the province and expand the EVT treatment time window, and 3) Focus on continuous quality improvement with electronic collection of variables that measure the elements of the stroke care pathway, aiming to minimize delays in time to treatment.Includes bibliographical references (pages 225-267
Sonic log depth series predictions using machine learning algorithms
No full textThis paper investigates the viability of predicting rock properties within wells using
real-time drilling data. Among these properties, the sonic log plays a crucial role
in understanding the physical characteristics of subsurface formations and helps geoscientists
and drilling engineers interpret the subsurface geology and make informed
decisions about well construction, drilling parameters, and reservoir performance.
Successfully forecasting sonic logs has the potential to significantly improve the optimization
of fracturing processes in wells with similar geological structures. To accomplish
this objective, we introduced a well-structured eXtreme Gradient Boosting
(XGBoost), LSTM (Long Short-Term Memory), and Random Forest (RF) models
that utilize depth-series data for predicting sonic log in the field of oil and gas exploration.
The data used in this research was gathered from the drilling project
“A Data Analytics Approach to Energy and Safety Improvements” which received
funding from the NL Offshore Oil and Gas Industry Recovery Assistance Fund.Includes bibliographical references (pages 140-145
A data grid strategy for non-prehensile object transport by a multi-robot system
No full textThe field of cooperative object transport within swarm and multi-robot systems
(MRS) is an interesting area of research because exploring the dynamics of how
multiple robots collaborate to transport objects presents fascinating opportunities
to advance the capabilities of robotic teams.
In this thesis we propose a control framework for non-prehensile object transport
using a multi-robot system. While an object can be unmanageable for a single robot
to push and transport, we demonstrate via simulations that a team of cooperative
robots can be used to transport such an object. The proposed control strategy is
divided into two phases: caging and cooperative transport. In the first phase, the
robots start from arbitrary positions and then approach the object to be transported,
forming a cage around it. The second phase consists of cooperatively transporting
the object ensuring that it remains caged during transport.
In the proposed strategy, the robots take a decentralized approach, wherein each
robot operates autonomously while maintaining indirect communication with other
robots. This is achieved by utilizing distributed data structures, such as distributed
locks, sets, and maps, offered by the concept of an in-memory data grid (IMDG).
By leveraging these distributed data structures, the robots can effectively share their
respective states with one another.
The key advantage of employing distributed data structures within our strategy
is that it eliminates the need to develop a new application-specific protocol for interrobot
communication. Instead, we can take advantage of the existing functionality
provided by the data grid, which offers a convenient mechanism for exchanging information
between robots.
To our knowledge, the utilization of an IMDG in the domain of MRS is a novel
concept. This thesis introduces a proposed design for a coordinated motion control
strategy specifically aimed at object transport. The strategy leverages the capabilities
of an IMDG, and presents it as a promising framework to simplify the communication
process among the robots involved, leading to improved coordination and optimized
object transport operations.
We showcase the results of our research using a realistic simulator that effectively
illustrates the viability of our method. This demonstration helps validate the effectiveness
and potential of our methodology in various environments.Includes bibliographical references (pages 49-58
TIGIT engagement impairs antiviral effector functions of CD8⁺ T cells from people living with HIV
No full textA persistent latent reservoir in long-lived CD4⁺ T-cells is the main obstacle to eradicating HIV-1 infection. Chronic HIV-1 infection functionally alters CD8⁺ T cells through upregulation of immune checkpoint receptors (ICs) such as T cell immunoreceptor with Ig and ITIM domains (TIGIT). Expression of ICs can result in impaired cytolytic activity and failure to suppress viral replication. Therefore, blocking IC receptors could be an adjunct therapeutic approach targeting the HIV reservoir in eradication strategies.
This study employed TIGIT engagement and blockade on CD8⁺ T cells from people living with HIV(PLWH) to test how TIGIT expression affects T cell function. We tested TIGIT engagement on CD8⁺ T cells from PLWH in non-specific redirected cytotoxicity assays and tested the impact of TIGIT blockade on HIV antigen-specific CD8⁺ T cells.
For PLWH with circulating CD8⁺ T cell cytotoxicity >10% in redirected killing assays, TIGIT engagement reduced cytotoxicity in 8/14 cases, showing that TIGIT engagement impairs killing by CD8⁺ T cells from some PLWH. About 20% of subjects tested by ELISpot had strong interferon-gamma (IFN)-γ responses against HIV Gag and/or Nef peptides (>1000 spot-forming units/106 peripheral blood mononuclear cells). Stimulation of HIV-specific CD8⁺ T cells with peptides in the presence of TIGIT-blocking mAb increased CD8⁺ T cell degranulation and IFN-γ production in certain individuals. Thus, generalized and HIV specific effector functions of CD8⁺ T cells from a subset of PLWH are inhibited by TIGIT expression.
These data show that TIGIT blockade can improve antiviral effector cell function in certain PLWH. Identifying features of the subset of responsive CD8⁺ T cells will help
direct blockade therapy to those PLWH most likely to benefit.Includes bibliographical references (pages 76-100