identifier: Natalie, Pavlik  (2022) Enfleshing Entanglements of Space, Time, and Matter Through Diffractive Artistic Processes: Conversations with my Late Great Nana Through Her Archival Journals.  Masters thesis, Concordia University.

abstract: Within this thesis I share the story of my entangled relationalities with my great nana, Dorothy, who passed away when I was three years old. Dorothy was a brilliant artist, and I grew up surrounded by her paintings that hang on the walls of my family home. Looking through these painted portals into Dorothy’s imagination throughout my life has greatly inspired my journey into becoming an artist, researcher, and teacher. Twenty-three years after her death, shortly before I began my graduate studies in art education, my family unexpectedly discovered a box of Dorothy’s archival journals, sketches, and photographs, within which she has documented her own various artistic processes. Within this inquiry, I explore Dorothy’s archival artistic processes through creating my own, expanding upon her past moments within my present pedagogic experiences, collectively weaving together a new story that defies boundaries, and enfleshes entanglements of space, time, and matter. As such, this research unfolds from the middle, through layers, rather than chapters, where past and future meet in the presence of becoming. This thesis both explores artistic processes and is composed as an artistic process in itself, rippling outwards from the present moment through various diffractive dimensions (Barad, 2007). Waves and undercurrents of meaning become increasingly dynamic as I investigate the pedagogic value of process through mapping an artistic process directly into the form and content of my inquiry.


identifier: Manouchehri, Narges ORCID: https://orcid.org/0000-0002-3011-5162 <https://orcid.org/0000-0002-3011-5162>  (2022) Generative learning models and applications in healthcare.  PhD thesis, Concordia University.

type: Thesis NonPeerReviewed

abstract: Analysis of medical data and making precise decisions by machine learning is emerging as a hot topic in healthcare. The ultimate goal of using these techniques is to transform data into actionable knowledge for supporting clinicians and improving patients quality of life. To assist health professionals in making precise decisions, clustering is among the most applied methods. This approach aims to stratify patients into meaningful groups based on their similarities in medical data spaces such as images, signals, and medical records. Among all clustering approaches, mixture models have been widely used by researchers in different fields due to their substantial flexibility to explain the data. Traditionally, Gaussian mixture models have been applied in real-world applications, but data are not Gaussian in many fields. In this thesis, we proposed novel clustering approaches based on finite and infinite mixture models. Our mixture models are developed based on a new distribution called multivariate Beta distribution which demonstrated lots of flexibility to fit data of different shapes. We paired our models with capable learning methods such as variational inference and expectation propagation. These learning methods determine the correct number of mixture components and estimate model's parameters which are two known challenges while fitting mixture models. Moreover, we modeled sequential data and developed a novel version of the hidden Markov model, namely multivariate Beta-based hidden Markov model, and extended it to a nonparametric model to increase its flexibility. All developed models are evaluated on real medical applications including medical images and signals. The outcomes demonstrated that our proposed models outperform similar alternatives.


identifier: Bansal, Vivek  (2022) A Framework for Estimating Vulnerability of Digital Circuits against Single Event Multiple Transients.  Masters thesis, Concordia University.

abstract:
Recent deep-submicron-technology-based integrated circuits (ICs) are substantially more susceptible to transient faults. Thus, the soft errors that occurred due to transient faults are more important than they have ever been. As a result, it is critical to identify any functional inconsistencies and component failures as early in the design process as possible in order to avoid potentially threatening events. Early stage analysis of the integrated circuits enables designers to build fault tolerant systems by applying some fault-mitigation techniques. Existing methodologies for investigating single event transients (SETs) or single event multiple transients (SEMTs) faults often lack the ability to perform system analysis due to the state-explosion (such as simulation-based testing) or due to the ignoring of post-layout information (such as netlist-based analysis).

In this thesis work, we develop a methodology to model and analyze the effect of transient faults at higher-level of abstraction. In the proposed methodology, we include the effect of SEMT on the integrated circuit (IC) device by considering its post-layout information. It also includes checking SEMT propagation throughout the circuit and the effect of all three masking factors (e.g. logical masking, electrical masking, and latching-window effect). The methodology also provides insights into  design vulnerabilities and critical areas of the IC layout.  It is further extended to estimate the vulnerabilities of registers in openMSP430 core while running a specific application.


identifier: Andam, Arian  (2022) Operating room planning with the pooling of downstream beds among specialties: A stochastic programming approach.  Masters thesis, Concordia University.

abstract:
In this research, we study a stochastic operating room planning problem with the possibility of restricted pooling of downstream beds among different specialties. Here, we suppose that there is a limited number of beds that can be shared among specialties. In this problem, surgical durations and patients’ length of stay are stochastic. We developed a two-stage stochastic integer programming model, where in the first-stage we decide on 1) the number of ICU and wards beds to be allocated to each specialty, and 2) the allocation of surgeries to operating rooms during the planning horizon. In the second stage, we decide on 1) how many shared beds in ICU and wards are allocated to which specialties on each day during the planning horizon, 2) the surge capacity required to satisfy downstream service to patients, and 3) the overtime incurred in each operating room during the planning horizon. The proposed model aims at minimizing the total cost including the patients’ waiting cost, postpone cost, overtime and fixed cost of operating rooms, and the cost of downstream surge capacity.
We have implemented the proposed stochastic programing model in a sample average approximation framework. We have carried out extensive computational experiments to evaluate the effectiveness of several pooling policies for downstream beds and also the efficiency of the proposed sample average approximation algorithm. We have also performed an extensive sensitivity analysis of cost and the stochastic parameters to provide managerial insights. Our results demonstrated that the sharing policy among different specialties in the downstream units enhance the functionality of the system up to 19.53%. Moreover, the results indicated that the solutions obtained by proposed stochastic model outperforms the solutions from the corresponding deterministic problem by 17.43% on average.


identifier: Singh, Sumeet  (2022) Permanent Magnet Machine Design with Cold Spray Magnets.  PhD thesis, Concordia University.

abstract:
With the global trend toward electrification of transport, the interest in various configurations of electric motors is growing. Surface permanent magnet synchronous machines (SPMSM) are used in many high-performance applications due to low inertia, high torque density, and overload capability. Several applications require low torque pulsations as they can lead to mechanical vibrations and acoustic noise in the electric motor. Various techniques have been proposed in the literature to reduce the torque pulsations either by using machine control strategies or by machine design. Optimization of the rotor permanent magnet (PM) shape is one of the effective methods for reducing torque pulsations. Unfortunately, the low versatility of the motor magnet fabrication technologies limits the development of new motor geometries. Current techniques used for the assembly of PMs in motors such as adhesives, slots, or screws are complex, labor-intensive, and offer very little flexibility for advanced motor design geometries. Consequently, alternative fabrication techniques such as cold spray additive manufacturing are worth exploring. Cold spray additive manufacturing is used for shaping PMs for the direct fabrication of electric motor parts without the need for additional assembly steps. This novel technique allows an increase in the design flexibility of electrical machine geometries targeting improved performance.

In this thesis, the PM rotors considered are the conventional rectangular-shaped with unskewed magnets (Model A), skewed magnets (Model B), and sinusoidal-petal-shaped magnets (Model C) along the axial direction. The magnitude of magnetization current pulse required to magnetize these rotors is calculated using an FEA package and an impulse magnetizer setup is designed and prototyped for in-situ magnetization. Various stator terminal connection configurations are analyzed and compared for the magnetizer. The performance of the shaped cold sprayed permanent magnet rotors and their effects on back EMF, electromagnetic torque, and cogging torque are analyzed experimentally and comparisons are made between the different rotor designs.

Laminated electrical silicon steel sheets are mainly used to produce the stator and rotor core of an electrical machine. In comparison, there are soft magnetic composites (SMC) which consist of a high purity fine iron powder particle coated with the insulation material. Hence, its electrical resistance is much higher than that of laminated steel. Its isotropic magnetic and physical properties help flux to conduct in a three-dimensional direction and effectively dissipate the heat produced from core losses. The product developed using SMC material uses compaction, heating, and pressing techniques to achieve the desired shape and final size of the machine core parts. Hence, the material wastage is lower as compared to the laminated steel core.

In this thesis, the impact of a few manufacturing parameters on SMC properties to ensure that optimized motor performance is achieved was analyzed using three SMC different materials (A, B, and C) using FEA software. Furthermore, machine design parameters are tuned to achieve optimal flux weakening. Finally, an FEA-based performance analysis of a 7.12 kW radial flux PMSM with laminated steel and SMC stator core is used to estimate the torque density and losses in the machines. Two different designs of 24/20 slot-pole and 12/8 slot-pole configuration using conventional surface permanent magnet rotor designs are considered. In addition, the ring-type Halbach-array PM rotor fabricated using cold spray additive manufacturing for 12/8 slot-pole is analyzed and optimized with the SMC stator core for high-speed electric vehicle application.


identifier: Fong, Kirsten Mei-Ling  (2022) Consumer Resistance and Resignation in the Age of Coerced Digital Participation.  Masters thesis, Concordia University.

abstract:
As society is increasingly reliant on data-driven technology, consumers are forced to provide their data to powerful tech companies through unilaterally imposed contracts to gain access to the technology needed to participate in society. Consumers are deeply discontent, cynical and resigned that their data will be collected and used in ways unknown to them. However, in an attempt to regain a sense of agency and protect their institutional and social privacy, consumers engage in everyday resistance practices based on three strategies: data strikes, conscious data contribution and data poisoning. This research contributes to the ongoing debate surrounding the privacy paradox, expands on our understanding of consumer resignation, provides novel insights into consumer resistance by framing privacy protection as an act of resistance and proposes a new understanding of the consumer in the discipline of marketing: consumer as the product and raw material. This work clearly supports previous findings that consumers reject surveillant marketing practices, suggests that companies with a privacy-first business model hold a competitive advantage, call into question the quality of the data collected and the subsequent profiles and models derived from this data and advocate for widespread privacy literacy education and strong privacy regulation.

Keywords: privacy, resignation, consumer resistance, surveillance, coerced digital participation, privacy paradox


identifier: LIU, YUPENG  (2022) Induction Machine Modeling and Emulation for Asymmetrical Conditions.  PhD thesis, Concordia University.

abstract:
The induction machine can be used as generator or motor, to convert mechanical power to electrical power or via versa. The induction generator is an essential element of many renewable energy systems such as wind power plants, etc. The induction motor is commonly adopted in industry. The advantages of induction machines are well-known compared to other types of machines. Thus, it is important to investigate induction machines with accurate models and replace expensive test benches and equipment by more efficient and economical test procedures.
To describe induction machines, different mathematical models have been devoted over the years to examine different problems. For instance, the abc frame model, dq frame model, hybrid model of abc and dq, and multiple coupled circuit (MCC) models. Based on those models, the developed model-based induction machine emulator is able to offer a flexible and easy platform for testing and analyzing characteristics of the induction machine in the laboratory environment. Therefore, accurate mathematical models are essential for further applications of induction machines.
Generally, the induction machine works under balanced conditions, but the unbalanced condition is inevitable in practice. Self-excited induction generator (SEIG) is a good option for standalone wind energy conversion systems and other renewable energy sources. In such SEIG systems, the majority of unbalanced cases occur due to load disconnection. On the other hand, the generator will have to supply nonlinear loads in most scenarios. Thus, the SEIG supplying three-phase unbalanced loads and nonlinear loads is relatively common.
Inside the induction machine, due to the combination of working environment, installation, and manufacturing factors, unbalance caused by internal faults can occur. Stator windings, rotor bars, and end rings are the most common internal faults. Such faults not only reduce the machine working efficiency and cause excessive heating but also cause potential hazards for continuous work and safety. As a result, it can lead to the failure of the machine.
Continuing to drive the induction machine with asymmetrical conditions can cause consequent failures and even permanent damage to the machine. This thesis proposes a power electronic converter-based machine emulator replacing the actual machine to investigate the performance of the machine under different kinds of asymmetrical conditions. The machine emulator provides a laboratory environment to test and analyze the characteristics of the actual machine, especially under critical operating conditions. Therefore, the risk, time and cost associated with generating real faults can be reduced, helping to overcome safety issues with actual faulted machines. Such techniques can also be applied in fault detection, diagnosis, and fault control areas. In this thesis, the emulation of a SEIG supplying unbalanced and nonlinear loads, an induction motor with stator winding faults and rotor cage faults conditions are researched.
The mathematical model of the SEIG system is established and the emulation results of balanced loads, unbalanced loads, transients during loading and nonlinear load conditions are compared with an actual SEIG system. The mathematical model of an induction machine with stator winding faults is also built. The emulator setup for a faulted induction motor is proposed and established, the experimental results of an actual machine with 5% and 10% faults have been done and then compared with simulation and emulation results. Different loading conditions are investigated. For the rotor cage fault induction motor, a novel machine parameter measurement method is introduced, which is able to measure the machine parameters without opening the machine, making it easier and more convenient to acquire rotor parameters. Usually, the faults inside the machine are hard to distinguish. In this thesis, the rotor cage fault is identified by analyzing the stator current frequency components, then the emulation setup is established. The simulation and emulation are compared with an actual faulted induction motor including loading conditions, which demonstrates the validity of the machine emulator.


identifier: Han, Ran  (2022) Panic Buying and Consumer-Brand Relationships.  Masters thesis, Concordia University.

abstract: Due to COVID-19, panic buying has spread around the world; thus, we need to have a better understanding of this phenomenon. Previous research has focused on the antecedents of panic buying. However, there has been a lack of research on how the consequences of panic buying impact consumer–brand relationships. More research has explored the impacts of negative emotions on consumer–brand relationships than the impacts of positive emotions (Khatoon & Rehman, 2021). This study explores the mediation effect of evoked post purchase positive emotions on the relationship between panic buying and brand relationships. The results of a survey of 401 Canadians 18 years old or above showed a positive relationship between panic buying and consumer–brand relationships and that positive emotions mediate this relationship. The findings of this article improve researchers’ and brand marketers’ understanding of the panic-buying phenomenon and the customer–brand relationship.


identifier: Mockler, Veronica  (2022) The Third Screen: For a Dialogic and Participatory Oral History.  Masters thesis, Concordia University.

abstract: Many researchers and artists turn to the field of oral history as an ethic and research practice because at its core lies the principle that we can better understand the world through listening and speaking to each other. By its very nature, oral history upholds the experience of someone who is not the researcher as being epistemologically worthy. Even within the academic setting, oral history maintains that those who know best are those whose knowledge has not been institutionalized. While through its very practice, oral history winds up institutionalizing what was voiced by participants, it understands that it must safeguard, through the record, their original voicing so that the subsequent institutional interpretation can be brought into question if need be. A video-documented research-creation project with four individuals who interviewed each other on their life experiences further deepened my thinking around this institutional interpretation and accountability. Through a three-screen video installation practice, informed by postcolonial theory and oral history’s popular education roots, I was able to directly include participants in the institutional interpretation of their interview. Articulating meaning from the interview and presenting results to a research audience are processes I achieved in dialogue with participants, rather than monologically. In the following text, I explore this multi-screen video practice and the dialogic opportunity it provides to oral history practitioners who believe in the epistemological significance of speaking and listening to other people.


identifier: Roman, Aurelia Loredana  (2024) Parent-School Interaction in a Post-Migration Context: An Analysis from the Perspectives of English-Speaking Single Mothers with Children Enrolled in the French-Language Public School System in Montreal, Quebec, Canada.  PhD thesis, Concordia University.

abstract:
Abstract
Parent-School Interaction in a Post-Migration Context: An Analysis from the Perspectives of     English-Speaking Single Mothers with Children Enrolled in the French-Language Public School System in Montreal, Quebec, Canada

Aurelia Loredana Roman, PhD
Concordia University, 2022

This study examines educational disadvantage in immigrant Canadian children and youth residing in the province of Quebec and attending public schools in the city of Montreal, a plurilingual, multiethnic, multiracial and multicultural city. Bronfenbrenner’s (1974, 1979, 1986) socio-ecological perspective of human development and intersectionality (Collins, 2009, 2015; Collins & Bilge, 2016; Crenshaw, 1991; Jiwani et al., 2021) were used to conceptualize the intersecting inequalities experienced by single-mother families in a post-migration context in Quebec. Inductive analysis of the data uncovers the unique challenges faced by single mothers in relation to their children’s education in Quebec, which has been largely neglected in the literature. Some of these challenges include linguicism, discrimination, racism, and inadequate pedagogical practices among multilingual immigrant youth in Accueil high schools.
The following insights emerge from interviews with twelve English-speaking immigrant single mothers: immigration is a feminist practice; urgent reforms are required to minimize educational injustices in Accueil schools; and a deceiving immigration environment is promoted by Canada and Quebec internationally.
Keywords: immigrant women; single mothers; educational disadvantage; immigrant Canadian children and youth; Quebec; immigrant Allophones; refugees; ethnocultural and racialized women.


identifier: Mohammad Mahdi, Nasiri  (2020) Investigation of Hollow and Dense Droplet Impact on Solid Surfaces.  PhD thesis, Concordia University.

abstract:
Droplet impact and its flattening on a surface play an essential role in many industrial applications such as inkjet printing, agriculture, and plasma spraying. Understanding the physics of droplet spreading is the key to maintaining the mass transfer process in all relevant applications. Two different problems are investigated in this study. In the first parts, the behavior of a hollow droplet after impact on a surface is considered, while in the last chapter, the effect of gas desorption on the flattening and solidification of a molten particle in investigated.
Most of the droplets observed in nature are dense droplets. Nevertheless, special droplets have been observed in several industrial applications such as aerosol transfer from the sea, oxygen dissolution, controllable biomedicine, and thermal spray coating which are called hollow droplets. In plasma spraying process, the accumulation of these flatten droplets (splats) on top of each other forms a coated layer. Due to their embedded medium, the cavity-containing droplets (hollow droplets) trigger cavitation when they reach the target and influence the splat properties by releasing the inner substance. However, it is difficult to study the impact and flattening of hollow droplets in thermal spraying, regarding the harsh environments, and phenomena small size and high velocity.
To better understand the flattening process of a hollow droplet, in this work, a comprehensive experimental, numerical, and theoretical study is performed on water and glycerol droplets impacting on a rigid surface. The experiments are repeated on different surfaces, including aluminum, sand-blasted steel, and superhydrophobic. The results show that the mechanisms of the post-impact process of hollow droplets are different from those of dense droplets in several aspects. We study the role of surface wettability, liquid properties, impact velocity, surface angle, and bubble size and location on the droplet flattening process. In the numerical part, compressible Navier-Stokes equations are solved using the volume of fluid (VOF) method. A theoretical model is developed to analyze the maximum spreading diameter of the hollow droplet impact analytically. Its prediction is in good agreement with the experimental and numerical results.
The comparison of simulation results with the experimental photographs shows that the numerical solver can correctly predict the hollow droplet shape evolution. It is demonstrated that flattening a hollow droplet has two significant distinctions compared to a dense droplet flattening. The first distinction is the formation of a counter-jet following the collision of a hollow droplet impact perpendicular to the surface. It is proven that the formation of the counter-jet is an inherent phenomenon of hollow droplet flattening and is unaffected by impact velocity or substrate angle. Nevertheless, it is revealed that the counter-jet length depends on droplet velocity or liquid viscosity. The second distinction is the ultimate shape of the flattened droplet. After contact on a hydrophobic surface, the dense droplet partially recoils toward the center and produces a dome shape. However, upon impact on a hydrophobic surface, the hollow droplet takes the form of a donut. This is owing to the perturbations caused by bubble rupture on the spreading droplet surface. As a result of these perturbations, the spreading liquid sheet is fragmented and, the droplet is unable to recoil toward the center, forming a donut shape. The results show that the spreading diameter and the counter-jet height formed after the hollow droplet impact grows with impact velocity increasing. Investigating the size and location of the entrapped bubble shows an optimum bubble size that facilitates the hollow droplet flattening. It is also demonstrated that the ripples on splats produced by the hollow droplets with a larger bubble size are higher than those of small bubbles.
In the end, the effects of surface gas desorption on the splat formation are studied. In plasma spray, the splats resulting from the impact, spreading, and solidification of molten particles are the building blocks of the spray coatings. Fragmented splats are formed on substrates held at room temperature and atmospheric pressure. Although the formation of a fragmented splat is attributed to adsorbates on the substrate surface, its dynamics have not been adequately addressed. In this study, a numerical model is developed to investigate the formation of fragmented splats during droplet flattening and solidification in plasma spraying conditions. Compressible Navier—Stokes equations are solved, and the volume of fluid (VOF) method is used to capture the liquid and gas interface. In addition, the source term method is used to capture the solidification process during droplet flattening.
Moreover, a new boundary condition is defined to consider the effect of gas desorption on the substrate surface after droplet impact. The numerical results show that gas desorption from the surface produces a barrier layer between the droplet and the substrate. This high-pressure region detaches the edge of the spreading droplet from the surface and forms a liquid sheet. The liquid sheet rises above the substrate and spreads up to 2 times more than droplets impacting surfaces without gas desorption. The fragmentation of the liquid film follows the overspreading of the droplet. As a result, only a portion of the initial droplet remains at the location of the impact, which forms a small solidified splat.


identifier: Asadollahkhan Vali, Ali  (2022) Airport Pavement Management System Assessing current condition and estimating remaining life from aircraft demand.  Masters thesis, Concordia University.

abstract:
ABSTRACT
Airport Pavement Management System
Assessing current condition and estimating remaining life from aircraft demand
Ali Asadollahkhan Vali
	Road pavements management system (PMS) is a well-established approach that could benefit airports. For the implementation of an Airport Pavement Management System (APMS), there is a need to assess current pavement condition by considering observed distress levels and to match such condition to an apparent age, hence enabling the estimation of remaining life.
Traditionally the use of a global pavement condition indicator (PCI) is deployed by airport agencies.  The estimation of PCI is done manually utilizing reference charts and tables. Automating this estimation is an imperative need. Furthermore, being able to predict the consumption of life by current and future aircraft demand (frequency and distribution) is key to airport operations.
AASHTO’s mechanistic empirical method was recalibrated to match fatigue after 20 years of operations of a case study on Mashhad International Airport in Iran. The method considers the fatigue damage analysis and includes various factors like aircraft traffic and their loadings and pavement structural parameters.
One of the objectives of this research was to automate the estimation of pavement condition index (PCI) based on observed distresses, facilitating the identification of damage and the association of remedial work. The second objective was to predict the pavement's remaining life by using the fatigue damage analysis technique by enabling the ability to predict pavement performance and the assumption that a pavement fails when the load repetition exceeds a certain threshold. By connecting both approaches, better decisions for the type of intervention and the timing of the intervention can be done.


identifier: Rostami, Ali  (2022) Stability analysis of frozen soil slopes considering strain localization.  Masters thesis, Concordia University.

abstract:
The study of frozen soil failure behavior has been a major issue to focus on over the past decades since the changing climate was known to be the main reason for the gradual degradation of permafrost (or frozen soil) in cold regions. The assessment of the variation of strength and deformation properties of frozen soils with temperature is very critical in geotechnical applications such as foundation design, slope stability analysis, etc. Over the years, many numerical, laboratory, and field studies have focused on characterizing the behavior of frozen soils at various negative temperatures. In this research, available studies in the literature are reviewed for characterizing appropriate temperature dependent strength and deformation parameters for the stability analysis of frozen soil slopes. Parameters including cohesion c, friction angle φ, Young’s modulus E, and Poisson’s ratio υ are determined as functions of negative temperature for three different frozen soils, i.e. clay, silt, and sand. These parameters are used as the input data for the 2D plane strain finite element (FE) modeling on the slope stability analysis at different temperatures and the Drucker-Prager (DP) model is applied as the yield criterion. The stability analysis is based on investigating the shear band development, considering strain localization at different temperatures. The results indicate that as the temperature decreases, the strength of slope against shearing and collapse increases. In cases where slope failure occurs, the plastic strain in the close vicinity of slope is significant, leading to developing a curved thin shear zone extending from the top to the toe of slope. This critical zone acts as the slip surface for the slope. At lower temperatures, in general, plastic straining throughout the domain decreases, and the critical shear zone would not develop completely, therefore lowering the possibility of slope collapse (=higher factor of safety). The numerical approach is capable of depicting the deformation and failure characteristics of frozen soil slopes sensitive to temperature changes.
Keywords: Frozen soil failure behavior, permafrost, uniaxial compression test, triaxial compression test, finite element (FE) MATLAB code, frozen slope stability, Drucker-Prager criterion


identifier: Djoko, Isaac Blaise ORCID: https://orcid.org/0000-0002-3689-4929 <https://orcid.org/0000-0002-3689-4929>  (2022) Interactions between people and forest elephants (Loxodonta cyclotis): the case of Campo-Ma’an National Park, southern Cameroon.  PhD thesis, Concordia University.

abstract: The aim of this research is to study human-elephant interactions for an integrated management of the landscape that maintains biodiversity while providing better coexisting conditions to human and forest elephants (Loxodonta cyclotis) in the Campo-Ma’an Technical Operational Unit. By combining social surveys and field investigations in three subdivisions, I first assessed the extent of wildlife damage to crops and identified the impact of human activities on wildlife. I found that almost all farmers suffered crop damages with considerable crops and economic losses attributed to forest elephants. Forest elephants therefore play a key role in people’s livelihood in the Campo-Ma’an landscape. Then, using camera traps and field investigations, I studied how forest elephants utilize the various land use types (National Park and Forest Management Unit both with various restrictions to human activities, and Community Land where some human activities are allowed) of this human dominated landscape. I found that elephants are attracted to areas with high species richness and increased fruits availability, both patchily distributed over the various land use types. However, forest elephants occurred mostly in community land dominated by human activities. Therefore, given the ongoing increase in human population in this landscape, the threats to forest elephant are expected to increase if no serious actions are taken by wildlife managers and administration. Furthermore, given their elusive nature, I investigated whether we could rely on local ecological knowledge, as compared to field investigation, to assess the diet composition and feeding habits of forest elephants. I showed that local ecological knowledge can be used to assess forest elephants’ most common and important food items. Indeed, the dietary profiles resulting from these approaches were concordant for most plant species. Finally, with the hope that beehive fences can be used to repel elephants from getting into farmlands, I studied the behaviour of local bees (Apis mellifera adansonii) in response to physical disturbance. I found a temporal variability in the aggressiveness of bee colonies, with their effect being minimal at night, suggesting beehive fences can only be used in combination with other mitigation measures in this area. Overall, further investigations are needed to suggest reliable measures for peaceful coexistence between forest elephants and humans in this landscape.


identifier: Deng, Zhiyang  (2022) A Droplet-Based Microfluidic Electrical Lysis Device using 3D Gallium Electrodes.  Masters thesis, Concordia University.

abstract: Most biological applications require access to the cell’s components and machinery and therefore a cell lysis step is required. Droplet-based microfluidics has the ability to perform millions of distinct biological assays on individual cells. Typically, droplet-based cell lysis is achieved in presence of chemicals, which is not compatible with most subsequent analysis. Electrical lysis is a rapid, simple, and compatible method to extract intracellular contents. However, very limited studies reported droplet-based electrical lysis. To fill the blank of this topic, we designed a droplet-based device with 3D liquid metal (gallium) electrodes configuration to achieve electrical lysis. This platform has been validated as a robust electrical lysis device with a lysis efficiency of ~ 99 %. The device is further examined for extracting plasmid DNA from E. coli cells. We propose that this system has the potential to be used for rapid cell lysis and extracting intracellular components on chip. In near future, CRISPR-based DNA assays will be performed to show the system can be utilized as a rapid detection device for specific biological application.


identifier: Mestry, Viraj Vinod  (2022) Lower Bound for the Duration of Event Sequences of Given Length in Timed Discrete Event Systems.  Masters thesis, Concordia University.

abstract: The Supervisory Control Theory (SCT) of Discrete Event Systems (DES) provides a framework for synthesizing a DES supervisor to ensure a DES plant satisfies its design specification. In SCT, supervisor synthesis is performed offline before the functioning of the plant. Generally, the size of the plant and the specifications models are large resulting in supervisors that need huge computer memory for storage -- usually unavailable in embedded systems. A solution to this problem proposed in the literature is Limited Lookahead Policy (LLP). In LLP, the supervisory control commands are calculated online during the plant operation. After the occurrence of each event, the next control command is calculated based on the plant behaviour over a limited number of events into the future. In practice such frequent LLP computation would not be feasible as multiple events can occur consecutively over a short duration, not leaving enough time for LLP computation between them. To tackle this issue, a method is proposed called LLP with Buffering where the supervisory control commands are calculated online and buffered in advance for a predefined window of events in future. Determining the correct size of the buffer is crucial in order to achieve a trade-off between the on-board memory requirement and the computational resources and also ensuring that new supervisor commands are computed before the buffer runs out empty. The size of the buffer primarily depends on (1) the execution time of the code for supervisor calculation and (2) the (fastest) rate of event generation in the plant. This thesis focuses on the second factor. Previously, the minimum execution duration of event sequences has been calculated experimentally. The experimental approach is not exhaustive and thus results in an overestimate in the value of the minimum execution duration of event sequences. In this thesis, a model-based approach to the computation of the minimum duration is proposed which begins by transforming the untimed model of the plant under supervision into a timed automaton (TA) by incorporating timing information of the events. Next, an exhaustive symbolic matrix-based search algorithm is proposed where all the event sequences from every mode of the TA model are traversed to determine the minimum execution duration of the event sequences. The proposed method avoids the reachability analysis of TA needed to determine the reachable clock regions for each mode. The number of these regions is exponential in the number of events. Instead, the method uses reachability on the graph of the untimed model (polynomial in the number of events). This algorithm runs faster but provides an underestimate for the minimum execution duration of event sequences. Next, a two-degree-of-freedom solar tracker system is used as a plant to analyse the timing behaviour of the events and the implementation of LLP with buffering. In this study, the model-based and experimental methods have been used together to choose a suitable buffer size. The resulting LLP supervisor with buffering has been successfully implemented.


identifier: FANG, ZIXI  (2022) A Novel Geometric Theory of On-Machine Tool Measurement and Practical, Optimal Approaches to Highly Accurate and Efficient On-Machine Measurement.  PhD thesis, Concordia University.

abstract:
Modern industry trends to smart machining that improves productivity at a low cost. The kernel technology of intelligent manufacturing is the automatic on-machine measurement (OMM). When applying OMM technology to computer numerical control (CNC) machines, in-situ measurement takes place in the machining environment without the need of unloading the tool and the part. However, adverse measurement environment, limitations on the efficiency of data capturing and processing, and diversified measured objects render efficient and accurate OMM very difficult. Holistic solutions are needed to advance OMM technology and therefore many scientific topics are involved. This work primarily focuses on geometric modeling of the on-machine cutting tool measurement and kinematic modeling for the calibration process of both the probe and the machine.

On-machine cutting tool measurement often takes place on a laser tool setter. However, the geometry principles of the gauging mechanisms of laser tool setters are complicated and had not been studied before. This dissertation modeled such a gauging mechanism and presented virtual simulations of the measurement processes on laser tool setters based on geometry principles. The virtual simulations can predict and compensate the measurement errors, allowing for accurate tool setter calibration processes in practical situations.

For cutting tool measurement, the tool length characteristic curve for measurement of round-insert mills is discovered. The derivation of the tool length characteristic curve was carried out by modeling the geometries of tool length measurement processes on a laser tool setter. Based on this characteristic curve, an accurate and efficient approach to measuring lengths of mills with round inserts and bottom cutting edge wear is proposed.

Current techniques for probe calibration and machine calibration assume the impractical situations where either the machine is accurate or the location of the probe is accurately known. To address these drawbacks, the actual kinematic model of a six-axis belt grinding CNC machine with a customized add-on probe is built in this dissertation. Using this model along with a specially designed artifact can facilitate the simultaneous calibration of the probe position and the machine geometry error.


identifier: Thomas, Henri  (2022) Smithy: A Bioinformatics Web Service for the Design and Comparison of Different DNA Cloning Procedures.  Masters thesis, Concordia University.

abstract: The field of Synthetic Biology has seen many recent developments in DNA assembly protocols, software tools in aide of assembly design and experiment planning, standardization of parts, and automation of complex and high-throughput DNA assembly and cloning processes. These software tools reduce human-introduced errors and the need for highly-skilled labor, cut-down the total cost of assembly experiments, and diminish the overall time expended in designing, planning and executing reliable cloning experiments. Shortcomings of these efforts, however, exist in their  usability and accessibility, support for major cloning methods, the incorporation of both part repositories and direct-synthesis DNA sequences in the design process, extensibility of the software, and the lack of a comparison of assembly design options offered by different assembly methods. Here, Smithy is presented: a web-application automating DNA assembly project design for scar-less assemblies, incorporating existing sequences from major repositories (e.g., AddGene and iGEM) and synthetic DNA sequences into the assembly design process. Currently, the supported cloning methods are Gibson, Golden Gate, PCR-SOE, SLIC and BioBricks. Smithy software architecture utilizes a new DNA cloning methods abstraction hierarchy, which facilitates effective and extendible application implementation and extendibility. Smithy’s graphical user interface and overall user experience are simpler and more informative than existing DNA assembly design tools. As a service, Smithy is open-source, free, and widely accessible for users of all experience levels. The core software features exist as independent modules that are portable to future automation projects. Furthermore, an analytical feature for creating assembly bundles, has been developed. Assembly bundles comprise of multiple assembly solutions for the same target construct; this facilitates quick comparison and selection of the most appropriate assembly solution by and for a particular user. To exemplify the usefulness of Smithy, two detailed case studies are presented: a single Gibson assembly for a riboswitch-modulated fluorescent genetic circuit, and another bundle assembly for an expanded riboswitch-modulated fluorescent genetic circuit, employing Gibson, Golden Gate and PCR-SOE methods. Finally, Smithy is a highly usable, future-oriented tool, which can be improved and expanded in response to future developments in cloning methodologies, standardization, and software tools, in the highly promising field of Synthetic Biology.


identifier: Ghoreshilangrodi, Seyedramin ORCID: https://orcid.org/0000-0001-7604-0226 <https://orcid.org/0000-0001-7604-0226>  (2022) Vorticity-Based Polynomial Adaptation for Unsteady Flows.  PhD thesis, Concordia University.

abstract:
Aerospace applications, including but not limited to the aerodynamics of slats and flaps, the aeroacoustics of complete landing gear configurations, and the performance prediction of air brakes, spoilers, fans, and turbines, benefit from high-fidelity scale resolving approaches such as direct numerical simulation and large eddy simulation. These approaches are shown to be accurate in complex unsteady flow regimes where current industry-standard Reynolds-averaged Navier-Stokes methods often fail. For example, recent research has demonstrated that direct numerical simulation can be utilized for analysis of complete jet engine low-pressure turbine cascades at their designed operating condition. High-order unstructured spatial discretizations such as flux reconstruction are particularly appealing for large eddy simulation of unsteady turbulent flows as they are capable of resolving the flow more efficiently; however, their computational cost remains relatively high, preventing their industrial use. Therefore, given the inherent computational cost of high-order methods, it is crucial to deploy strategies to minimize the overall computational cost of large eddy simulation while attaining comparable accuracy. A practical approach is to limit the use of high-order elements to regions where higher resolution is required for an accurate discrete approximation of the solution, reducing the total number of degrees of freedom. This can be achieved by locally increasing or decreasing the solution polynomial degree to adjust resolution and order of accuracy to achieve an accurate and cost-efficient simulation, a practice called polynomial adaptation or p-adaptation. Large eddy simulation can also benefit from the computational power of state-of-the-art hardware architectures by taking advantage of parallel computing, which can achieve a significant speed-up by decomposing the domain and solving the problem concurrently. Parallel computing also provides a larger memory capacity and higher bandwidth, resulting in better performance. However, combining polynomial adaptation with a massively parallel computation can cause overhead because p-adaptation tends to change the degree of solution polynomials locally, leaving the computational domain unbalanced. To maintain parallel efficiency, dynamic load balancing techniques have been exploited. The current work introduces a novel dynamically load-balanced polynomial adaptation method for simulations of unsteady flows in the vicinity of complex geometries using the flux reconstruction scheme. This approach is applied to both two-dimensional and three-dimensional studies, while for the latter, we make use of implicit large eddy simulation, which relies on the dissipation error of the numerical scheme to act as a subgrid-scale model to dissipate the kinetic energy from the smallest turbulent scales in the flow.

We verify the utility of our dynamically load-balanced adaptation approach when applied to the arbitrary Lagrangian-Eulerian form of the compressible Navier–Stokes equations for a range of applications on moving and deforming domains. Specifically, we verify the arbitrary Lagrangian-Eulerian and dynamic load balancing implementation by performing simulations of an Euler vortex, and then illustrate the accuracy and efficiency of the adaptation routine by performing simulations of flow over an oscillating circular cylinder with two different flow settings, dynamic stall of a 2D NACA 0012 airfoil undergoing heaving and pitching motions, and flow over a vertical axis wind turbine composed of two NACA 0012 airfoils. We further illustrate the accuracy and efficiency of the routine when applied to transitional and turbulent flows by performing simulations of a shallow dynamic stall of a 3D SD 7003 airfoil undergoing heaving and pitching motions and transitional flow over a 3D circular cylinder. Results demonstrate that the dynamically load-balanced adaptation algorithm can track regions of interest, such as vortices and boundary layers, and yields a significant speed-up when applied to parallel simulations. We also demonstrate the scalability of the algorithm and the capability of dynamic load balancing technique to distribute uniform computational load among processors.


identifier: Khloponin, Pavel  (2022) Vector Space Proximity Based Document Retrieval For Document Embeddings Built By Transformers.  Masters thesis, Concordia University.

abstract:
Internet publications are staying atop of local and international events, generating hundreds,
sometimes thousands of news articles per day, making it difficult for readers to navigate this stream
of information without assistance. Competition for the reader’s attention has never been greater.
One strategy to keep readers’ attention on a specific article and help them better understand its
content is news recommendation, which automatically provides readers with references to relevant
complementary articles. However, to be effective, news recommendation needs to select from a
large collection of candidate articles only a handful of articles that are relevant yet provide diverse
information.
In this thesis, we propose and experiment with three methods for news recommendation and
evaluate them in the context of the NIST News Track. Our first approach is based on the classic
BM25 information retrieval approach and assumes that relevant articles will share common key-
words with the current article. Our second approach is based on novel document embedding repre-
sentations and uses various proximity measures to retrieve the closest documents. For this approach,
we experimented with a substantial number of models, proximity measures, and hyperparameters,
yielding a total of 47,332 distinct models. Finally, our third approach combines the BM25 and the
embedding models to increase the diversity of the results.
The results on the 2020 TREC News Track show that the performance of the BM25 model
(nDCG@5 of 0.5924) greatly exceeds the TREC median performance (nDCG@5 of 0.5250) and
achieves the highest score at the shared task. The performance of the embedding model alone
(nDCG@5 of 0.4541) is lower than the TREC median and BM25. The performance of the combined
model (nDCG@5 of 0.5873) is rather close to that of the BM25 model; however, an analysis of the
results shows that the recommended articles are different from those proposed by BM25, hence may
constitute a promising approach to reach diversity without much loss in relevance.


identifier: Schott, Esther  (2022) Budding bilinguals: Investigating bilingual infants’ language acquisition.  PhD thesis, Concordia University.

abstract:
Almost one in six children in Canada grow up hearing two languages. Bilingual children frequently encounter switches between their languages, and must learn words in both. My thesis tackles three central issues of early bilingual language development.
Manuscript 1 investigated whether infants can detect language switches at the level of individual words. This ability could help infants cope with rapid language switching in their language input, and prepare them, once they start speaking, to have control over which language they use. I tested bilingual and monolingual 8- to 12-month-olds’ interest in single-language trials (“milk…dog”) and switched-language trials (“milk…chien”). Neither group showed evidence of differentiating between contexts, suggesting that detection of single-word language switching is more difficult than previously assumed based on prior research investigating multi-sentence language switching.
Manuscript 2 examined whether infants can associate a person with the language that person is speaking. Some theories of early bilingualism propose that person–language associations help infants navigate their bilingual language input. I tested 5- to 18-month-olds’ surprisal when a speaker switches to a different language. Results showed no evidence that infants spontaneously associate a person with a language. This contrasts with common but outdated advice to caregivers to choose a single language when speaking to their child, and is consistent with research showing that bilingual infants learn languages from a variety of family language strategies.
Manuscript 3 examined how bilingual infants mentally represent the sounds in familiar words. Bilingual and monolingual infants were tested to examine whether bilingual infants are more or less sensitive to mispronunciations than monolinguals. I tested 24- to 26-month-olds in a looking-while-listening task. I found a robust mispronunciation effect in bilingual and monolingual toddlers, indicating that bilinguals’ encoding of sounds in familiar words is phonetically detailed in a similar way as monolinguals’, despite bilinguals having to navigate a more complex phonetic environment.
In these three manuscripts, I found that bilingual language acquisition is similar to monolingual development in many aspects, and rigorous testing of assumptions about bilingual language acquisition is needed to learn about the mechanisms bilingual infants use to acquire language.


identifier: Singh, Tanya  (2023) Exploring Novel Antecedents and Consequences of Choice Deferral.  PhD thesis, Concordia University.

abstract: This dissertation explores novel antecedents and consequences of choice deferral. Choice deferral is a common consumer phenomenon wherein consumers put off making choices due to choice conflict during a decision task. In the first chapter, I summarize extant research in choice deferral and describe research in the related domains of procrastination and choice delay. Based on existing research, I propose a novel consequence of choice deferral. In chapter 2, I examine the impact of choice deferral on deferral on subsequent unrelated choice tasks. Across four studies, I find evidence for a novel “deferral momentum” effect, such that initial choice deferral begets subsequent choice deferral. I examine decision confidence as a potential mechanism of this effect and find evidence to support my predictions. Finally, in the chapter 3, I investigate how the degree of choice conflict on initial choice impacts subsequent choice deferral. Across four studies, I find that choice conflict can counterintuitively decrease incidence of choice deferral. I argue this occurs because a conflict mindset can facilitate evaluation of contrasting information and attributes, thus facilitating tradeoffs and reducing deferral. My dissertation aims to expand our understanding of how choice deferral and its determinants can impact subsequent choices. My findings have important implications, both for consumer behavior scholars and marketing practitioners.


identifier: barhoumi, oumaima  (2022) Formal Analysis Of Traffic Conflicts Severity Using Keymaera.  Masters thesis, Concordia University.

abstract:
Evaluating traffic safety based on crash data is deemed unreliable due to the scarcity of the reported crashes. Furthermore, the process of accumulating a dependable database can take years to be achieved. As an alternative, surrogate safety measures such as Traffic Conflict Techniques (TCTs) are emerging to address many shortcomings of the crash data analysis. However, using data-centric approaches such as simulation to identify traffic conflicts events leading to crashes limits the confidence in road safety assessment. With formal verification, improving traffic safety by accurately analysing traffic conflicts is guaranteed thanks to the mathematical basis and rigorous analysis nature of formal methods.

This thesis aims to complement conventional data-oriented methods for traffic safety assessment with the formal verification of safety properties using the KeYmaera theorem prover based on differential Dynamic Logic (dL). Our main focus is to guarantee the safety of road users through the evaluation of traffic conflicts and providing safer traffic interactions between vehicles. Towards achieving this goal, we propose a set of traffic safety properties based on the combination of different TCTs, i.e., time-to-collision (TTC), space headway (SHW), shockwave speed (SWV), extended delta-V ($\Delta$V) and deceleration rate, along with evasive actions indicators, i.e., jerk profile and yaw rate. The aim of these properties is to formally analyse traffic conflicts in order to determine their severity as well as set accurate traffic conditions to ensure the traffic safety.

In another effort to validate the property linking TTC, SHW and SWV, we use SUMO (Simulation of Urban MObility) on a real-life dataset. Thanks to this traffic simulator, the vehicles dynamics are extracted and a list of TCTs is also provided for every time step. In order to realize a traffic management process, Mathematica is used to interface with SUMO, identify vehicles violating the stated safety property and conduct a speed-adaptation control process to update vehicles’ speeds.


identifier: Fenster, Richard  (2022) A Network on Chip For Concurrent Transmission Of Accurate and Approximate Data.  Masters thesis, Concordia University.

abstract: As time passes by, there is an increase in desired computational ability. Networks on chip have been seen to facilitate communication between tightly coupled processing elements located on the same die. With said increasing computational demand, comes an increase in power consumption. As a result, approximate computing techniques are used in conjunction with networks on chip to reduce power consumption and latency. When implementing these approximate networks on chip, additional resources are required and may not have maximal use during runtime. In this work, we propose a network on chip design that maximizes resource usage irrespective of data type. This is achieved by using virtual channels that are configured depending on one of two operating modes. An accurate only mode allocates all bandwidth such that a single accurate link is active. The other operating mode is a mixed mode where the bandwidth is halved for approximate and accurate data types. If operating in this mixed Mode, a latency reduction of up to 4.2% from baseline can be realized when approximate traffic accounts for sixty-seven percent of all network traffic. The additional power requirement for this improvement is 22.6% when wide flits are used.


identifier: Rezazadeh Mehrjou, Rameh  (2022) The Effects of Current and Past Health Status on Wages.  Masters thesis, Concordia University.

abstract:
In this paper, I analyze the impact of health status on the wages of men and women in National Longitudinal Survey (NLSY79) from 1979 to 2018. In doing so, I use self-assessed health status as the health measurement and address the potential endogeneity problem of
health status in the wage equation by considering a fixed-effects model. The results of the fixed-effects model are compared to those of a random-effects model. The analysis involves not only the impact of the current health status but also the impact of the health status of
the previous year on current wages. The findings in this paper suggest that poorer health status of time t means lower wages for both White and non-White workers. The lagged effect of health status on wages is higher for women than men. The results are robust across race
and gender groups.


identifier: Roussac, Alexa  (2022) Physical and Psychological Effects of Combined Motor Control and Isolated Lumbar Extension Exercise Versus General Exercise for Chronic Low Back Pain: a Randomized Controlled Trial.  Masters thesis, Concordia University.

abstract:
Exercise is the most common treatment approach for patients with chronic low back pain (LBP) and its psychological factors should also be considered given their known negative influence on recovery. Motor control and general strengthening exercises are two commonly used exercise therapies for chronic LBP, yet few studies have examined both the physical and psychological effects of these exercise interventions on chronic LBP. The purpose of this randomized controlled trial (RCT) was to compare the effectiveness of combined motor control and isolated lumbar extension exercises (MC+ILEX) versus general strengthening exercise (GE) on pain, disability, and psychological factors in patients with chronic LBP.
A total of 50 participants with LBP were randomly assigned to each group (n=25 per group). Both groups received 2 supervised exercise sessions for 12-weeks. Outcomes measures were obtained at baseline, 6-week and 12-week and included pain intensity (NPRS), disability (ODI), depression and anxiety (HADS), pain catastrophizing (PCS), Kinesiophobia (TSK) and insomnia (ISI). Repeated measures ANOVA was used to assess the main effects of group, time, and group*time.
There were no significant differences between groups for any outcome at any time point. Participants in both groups had significant improvements in NPRS, ODI, and TSK (all p<0.01) scores from baseline to 12-week. Participants in the MC+ILEX group also had significant improvements for PCS (p=0.04).
Our findings indicate that MC+ILEX and GE have similar positive effects in patients with chronic LBP. Both exercise interventions were effective to improve pain, disability, and psychological factors.


identifier: Rye, Meaghan  (2022) Effects of Combined Motor Control and Isolated Lumbar Strengthening Exercises on Multifidus Muscle Morphology, Function, and Physical Disability in Chronic Low Back Pain.  Masters thesis, Concordia University.

abstract:
Introduction
Low back pain (LBP) is the leading cause of disability and a major public health concern. Literature generally supports the effectiveness of exercise therapy for the treatment of chronic non-specific LBP, but there have only been modest effects. Considerable evidence suggests a link between lumbar multifidus degenerative changes and functional deficits. Recent preliminary evidence suggests that motor control and targeted lumbar extensor strength training may lead to hypertrophy and reduce fatty infiltration, however the optimal exercise intervention for reversing these changes is unknown.

Objectives
To study the effects of combined motor control and extensor strengthening on multifidus morphology and function, and to determine how physiological changes relate to pain, function, and psychological factors.

Participants
The study included 25 participants aged 18 to 65 with moderate-to-severe chronic non-specific LBP.

Intervention
Participants completed a 12-week supervised motor control and isolated lumbar extension intervention at a frequency of two times per week.

Measures
Primary: multifidus morphology
Secondary: multifidus function, lumbar extensor strength, pain, self-reported outcomes

Results
There were significant increases in the paraspinal CSA at L4-5 and L5-S1 between all timepoints and significant decreases in %fat fraction of multifidus and erector spinae at L5-S1 between baseline and both 6 and 12-weeks. There were significant increases in multifidus thickness and lumbar extensor strength between all timepoints.

Conclusion
Our results suggest that an intervention combining motor control and isolated lumbar extensor training has the potential to be successful in improving a large variety of outcomes, both physiological and clinical, in patients with chronic LBP.


identifier: Carlisi, Tina  (2022) Intimacies: A Feminist Exploration of Squatting Utopias Through Field Research and Art Practice.  PhD thesis, Concordia University.

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abstract:
My doctoral research is a feminist, utopian exploration of three squats through field research and art practice. Squatting is unlawfully occupying vacant or unused buildings or land without the owner’s permission, to create a collective living environment and/or operate a social centre where culture, political organizing, social events, and DIY skills are shared and accessible to a wider community. For three months in autumn 2017, I was a guest, volunteer, and artist-researcher at three squats: the former protest camp Grow Heathrow (est. 2010, evicted/demolished 2021) in London; Can Masdeu (est. 2002), a squat in a former hospital and surrounding gardens in Barcelona, abandoned since the sixties; and Freetown Christiania (est. 1971), founded by squatters on a former military base in central Copenhagen. Situated in three distinct cultural and social contexts, these autonomous communities, and the experiences of the individuals who live there, share many similarities.

My field research involved case studies, field notes, interviews with women squatters, and research-creation informed by feminist oral history and a personal utopian exploration of each site, to investigate intimacies at the intersection of communal living, learning, and creativity. By intimacies, I refer to: a) social intimacies: togetherness or closeness; and (b) material intimacies: closeness through skill-sharing and re-skilling. Developed in parallel and in dialogue with my fieldwork, I created a book of poems and drawings called Intimacies, intended to articulate the emotional knowledge of this research: what intimacy feels like in these community contexts, from my artist-researcher perspective. Intimacies is a seventy-two-page, two-colour, Risograph-printed artist’s book of handwritten poems and drawings, which I first developed when visiting these communities. This research uses poetic writing as an active tool and a deep phenomenological probing to approach the complex, subtle experience (Kusserow, 2020) of autonomous collective living. Through a poetic window, I investigate how such experiences, as they impact an individual’s personhood, may be creatively expressed. A broader goal of this research is to consider how communal life in these squats can reimagine the world in crucial ways, especially pertaining to the ongoing global COVID-19 pandemic, when offline and intimate communality seems increasingly unattainable.


identifier: Singh, Parul  (2022) Corporate social responsibility in India: Mandatory vs. voluntary investments.  Masters thesis, Concordia University.

abstract: As corporate social responsibility (CSR) becomes increasingly relevant, India has moved from a voluntary regime to a mandatory one. This paper examines the CSR expenditure compliance of 490 publicly listed companies from 2014 to 2021 (i.e., the post-voluntary regime period) and explores the causes and consequences of firms making additional voluntary CSR investments. We analyze various firm characteristics, including price volatility, employee welfare, cash flows, and political party donations, to explore why some firms spend more on CSR than others and exceed the mandated CSR investment threshold. Our findings demonstrate that CSR expenditures provide various advantages to firms. Higher CSR activity reduces stock price volatility and improves employee performance with a reduced cost. However, CSR expenditures require higher ex-ante liquidity. Our results also show that firms that make political donations tend to be more socially responsible. The latter finding is of particular interest because it contrasts prior findings that have found CSR expenditures and political contributions to be substitutes rather than complements.


identifier: Groves, Veronica  (2022) The effect of abiotic and biotic stressors on the cognitive ecology of Trinidadian guppies, Poecilia reticulata.  Masters thesis, Concordia University.

abstract: Freshwater fishes are threatened by anthropogenic disturbances such as increased temperatures and turbidity. These abiotic stressors can have important impacts on behaviour, physiology and cognition, but how these stressors can interact with predation risk, a pre-existing biotic stressor, have yet to be explored. In this study, we experimentally exposed Trinidadian guppies (Poecilia reticulata) to increased predation risk and increased temperatures (experiment 1) and to increased predation risk and increased turbidity (experiment 2). This allowed for the exploration of the isolated and interactive effects of multiple stressors on neophobia, the fear of novelty, and learning of novel predator cues. Using a 2x2 design, guppies were exposed to high vs low levels of disturbance (temperature or turbidity) combined with high vs low levels of predation risk over one week. We then tested for their impacts on neophobia and learning. Guppies exposed to increased temperature and increased risk (experiment 1) in tandem displayed an increase in antipredator behaviours to a novel versus risky stimulus. However, in contrast, guppies exposed to increased turbidity and increased risk (experiment 2), both as single stressors or combined stressors, displayed increased antipredator behaviours to risky than novel stimuli. Surprisingly, individuals exposed to both increased temperatures and increased predation risk exhibited learning suggesting that learning of novel predator cues may convey a selective advantage under highly disturbed conditions. In contrast, guppies exposed to increased turbidity and/or increased predation risk in experiment 2 did not exhibit learning with perhaps turbidity lowering the perception of predation risk. Taken together, our findings suggest that interactions between abiotic stressors, namely temperature or turbidity, and predation risk can impact learning of novel predator cues, and to a lesser extent neophobia.


identifier: Torres, Cecilia  (2022) Experiencing Leisure Kits in Relation to Art Education: A Research Creation Project.  Masters thesis, Concordia University.

abstract: Artistic leisure kits, such as paint by numbers, became a popular item in demand throughout the pandemic. As I was dealing with the anxiety of uncertainty and the overwhelming amount of information, I decided to investigate the popularity of leisure kits and their possible incorporation as a transitional strategy within an art classroom. People writing about these kits claimed they might fulfill the newly acquired leisure time that appeared due to the mandatory isolation, while simultaneously releasing tension and dissipating overthinking. Due to their increasing popularity, I wanted to find out what people experience when working with leisure kits, and if they might help lead to creativity. My research question was, does completing leisure kits provide any learning outcomes, and if so, what are those outcomes? Using research-creation methodology and heuristics, I discovered the potential of leisure kits for the increase of confidence and motivation, the experience of flow, and the decrease of art anxiety that support the creative process. I immersed myself in the process by completing three different types of kits to gather information through the discovery phases. In parallel, I interviewed the people who inspired me to explore this avenue, specifically, those who tried kits for similar reasons I did. The interviews allowed me to gather additional information about their thinking process through making, their potential learning experience, and the results achieved. Learning outcomes also emerged, such as problem-solving skills, motor stills, and the questioning of pre-conceived notions of art practice and the necessary skills to achieve them.


identifier: Clark-Combot, Julia  (2022) There are Two Worlds: An Investigation of Childhood, Adulthood, and Influence in Philip Pullman’s His Dark Materials trilogy.  Masters thesis, Concordia University.

abstract:
Despite its polemical anti-authoritarian stance on religion, Philip Pullman’s children’s fantasy trilogy, His Dark Materials, edifies the ideological separation of adult and child. The primacy of so-called adult characteristics reflects the influence of authoritarian ideologies on Pullman’s writing. In the study below, with a special focus on the essentializing developmental framework Pullman deploys to structure Lyra’s growth from childhood to young adulthood, I show how the HDM trilogy replicates many of the frameworks it disavows. Building on existing scholarship, I present the broader influence of Christian values on Pullman’s trilogy despite his
antagonism towards Christianity’s impact on children’s literature. Additionally, while acknowledging Pullman’s rebellion against the frequently religious generic conventions of children’s literature established by J.R.R. Tolkien and C.S. Lewis, I expand on this connection to argue that Pullman’s disdain for fantasy is connected more broadly to the history of children’s literature and colonialism, and that this interplay highlights the ongoing connection between empire and the English canon which complicates Pullman’s anti-authoritarian and anti-theistic quest for a republic of heaven in the His Dark Materials Trilogy. By connecting Lyra’s developmental trajectory to the influence of Christianity and imperialism within the institutional norms of education, children’s literature, and psycho-medical discourses, I ultimately argue that
we should be skeptical of the developmental model HDM proposes, and the values it upholds.


identifier: Ristola, Jacqueline ORCID: https://orcid.org/0000-0003-2186-8717 <https://orcid.org/0000-0003-2186-8717>  (2022) Cartoon Networks: Animation and Conglomeration from Turner to AT&T.  PhD thesis, Concordia University.

abstract:
This dissertation examines how the aesthetics of popular American television animation transformed as its distribution shifted from cable to digital platforms across eras of media conglomeration from the 1990s to the present. I argue that the understudied object of television animation offers new perspectives on the history of the American television industry. To accomplish this task, I use the methodology of “looking for loops” to trace the media logic of media conglomerates as they manifest in cultural production. This dissertation focuses specifically on animation made for television, typically called limited animation, as the production of this specific form of animation is indelibly entwined with its distribution on the medium of television. Logics of conglomeration here refer to specific assumptions that shape media production within conglomerate structures.
	Chapter 1 analyzes American trade press archives to illustrate how animation’s transition from film to television in the 1950s radically altered animation aesthetics. It demonstrate how television animation’s “limited animation” techniques—responsible for television animation’s signature look—created archives of footage that content-hungry cable networks could remix in the 1990s. Chapter 2 discusses the popular animation cable channel Cartoon Network over its history from the 1990s to the mid-2000s in order to analyze how content curators develop animated worlds to facilitate intellectual property cross-overs in the U.S. and Mexico. Chapter 3 analyzes press reports and platform interfaces to demonstrate how corporate strategy in the streaming era of the 2010s restructures the production and distribution of animated programs. Chapter 4 symptomatically reads cultural production under conglomerate ownership of AT&T, tracing how these productions reflect corporate ambitions and anxieties around digital media distribution. The conclusion ends the dissertation by situating animation’s role in what tech and media giants project as the future of media: the “metaverse.” It demonstrates how animation helps realize these ideas of virtual space, using platform studies and queer phenomenology to argue that the metaverse expands animation into a framework for building media platforms.


identifier: Rahimi, Narges  (2022) Microbial Electrochemical Systems for Enhanced Wastewater Treatment and Energy Recovery.  Masters thesis, Concordia University.

abstract: Technologies like bio-electrochemical systems (BESs) can play a significant role in simultaneously treating waste materials and energy recovery. In this research, three kinds of BESs, including single-chamber (SCMEC) and dual-chamber (DCMEC) microbial electrolysis cells and microbial fuel cells (MFC), have been examined as wastewater treatment pathways in urban areas. The mathematical modeling of the mentioned technologies is carried out, and the models are implemented using the Python programming language. The results show that the hydrogen production rate in SCMEC is less than in DCMEC because of hydrogenotrophic bacteria activities, which are reported as about 0.86 m3 and 0.56 m3 of H2 gas per m3 of wastewater, respectively. Also, the model analysis shows that applied potential and anode surface area directly affect hydrogen production rates SCMEC and DCMEC. The calculated electric energy output was 0.033 kWh per m3 of wastewater for the MFC. Two real case studies in Montreal have been considered to investigate the potential of using the mentioned systems on an urban scale. The first district, including residential buildings, has a total daily wastewater generation of 3,000 m3/day, and 75 m3/day is assumed for the second one with a smaller non-residential building project. The model is estimated that 141 kg and 230 kg of hydrogen can be generated via SMEC and DMEC, respectively, and through the second scenario, 2.5 kWh energy can be extracted from wastewater via MFC. In the next stages, the results shown by considering the recovered energy via BESs, WWTPs consume energy to treat the same amount of wastewater compared with BESs. Also, DCMEC and SCMEC have been compared with water electrolysis (WE) technologies for hydrogen production. So, the comparisons expose that for generating one kg of hydrogen gas, DMEC is more efficient than SMEC and WE. In addition, the feasibility of using the generated hydrogen and power via microbial systems as fuel in green cars has been investigated as a final step.


identifier: Reza, Rajaei  (2022) Design and Implementation of Integrated Smart Home Energy Management Systems for Clusters of Buildings.  Masters thesis, Concordia University.

abstract: To ensure the balance between power generation and demand at the peak hours, power utilities need to keep additional power generation capacity on standby which usually causes higher operational cost. This will result in variations in hourly to seasonal electricity prices. With a focus on the physical layer integration, we developed a methodology which includes a prototype of a cluster of smart homes with energy management systems (SHEMS) to study and harvest the flexibility in the demand side in the residential building sector by monitoring and controlling the loads at appliances level. For this goal, we developed and fabricated the electronic circuit of five custom-designed smart plugs (DC, MQTT based) and integrated a vendor-based smart plug (AC) to the system. The devices were equally allocated to three home hubs. As opposed to a standalone SHEMS, this methodology is applied at a cluster scale: through awareness of the electricity consumption of all houses, under certain assumptions optimized load patterns can be generated not only to decrease consumers’ electricity bills, but also to meet the grid’s constraints. We crafted 3 scenarios as showcases of the methodology performance, with two electricity price plans and different load configurations. The results show both smart plug types were successful in measuring the loads and communication with other layers resulting in decreased electricity cost. Additionally, using a hybrid cloud-fog based architecture, a function was designed for saving the smart plugs records during cloud service or internet disconnection to enable later synchronization of the local and cloud database.


identifier: Giahi Foomani, Matin ORCID: https://orcid.org/0000-0002-8566-6324 <https://orcid.org/0000-0002-8566-6324>  (2022) Assessing the Impact of Active Signage Systems on Driving Behavior and Traffic Safety.  PhD thesis, Concordia University.

abstract:
Unsignalized Stop-Controlled Intersections (SCI) are widely used in North America, and account for one out of every ten collisions. Understanding how drivers and pedestrians behave at unsignalized intersections is critical for public safety. Drivers who do not obey the stop-sign’s indication by not coming to a complete stop or miss or fail to stop at SCI create a substantial safety risk. For decades, visibility and placement of road alignments and signage at intersections have been a concern among transportation safety specialists. Deployment of backlit Light-Emitting Diode (LED) or other illuminated signs (also known as active road signs) has been increased especially at hot-spots and locations with known safety problems, or potential collision risks. While these signs are expected to improve safety measures by regulating safe travelers’ passage, their performance is not yet fully understood. Although environmental factors such as intersection type, location, and road design are playing a major role, compositional variables such as driver behaviour, which can be explained in terms of carelessness, lack of attention, or overconfidence, is resulting in a failure to comply with the law of making a complete stop at SCI.
Previous empirical research demonstrated some correlation between several variables such as traveller compliance with road signs and alignments, direct and indirect road safety measures, collision/conflict frequency, and road/traffic characteristics. These studies commonly employ before-after or cross-reference analyses to determine the long-term effects of various countermeasures at SCI. A few studies also utilized calibrated micro-simulations models to evaluate the surrogate safety measures at SCI.
This thesis defines a methodology to evaluate the safety performance of a new and untested signage without putting traffic at long risk. To evaluate the performance of the signs, the suggested methodology investigates multiple parameters and identifies influencing variables in a conflict-based collision-prediction model at SCI. The proposed methodology is applied to a real-world network in the city of Montreal, with several three-leg SCI equipped with different countermeasures. The experiment was designed in a fashion which isolates the influence of several variables, allowing the focus to be on the impact of the target variable (signage type). Field experiments have been performed to study the driver’s behavior in terms of approaching speed as well as quantitative analysis on reactions to various signs, using different sample groups from the same population. This research sets up a microsimulation model that captures drivers’ behaviour with respect to signage according to the observed data. A genetic algorithm was deployed to calibrate the microsimulation model in terms of turning movement counts and the critical conflicts were calculated at each intersection using vehicle trajectories. Collision-prediction regression models was then developed for the intersections under investigation, using traffic volume and conflict.
The results demonstrated a high correlation among countermeasures and drivers’ speed and compliance. The relationship between critical conflicts computed in microsimulation models and actual collisions was found to be statistically significant. The model which includes drivers' compliance in collision-prediction regression was also found to fit the collision data better. However, the results of this study do not support the previous assumption that the conflict-based collision-prediction models fit the collision data better than the volume-based collision-prediction models at SCI, especially with drivers’ compliance supplementary data. Finally, while the backlit signs’ performance was marginally better than that of a normal LED active sign, the difference was not statistically significant.
The methodology suggested in this thesis has the potential to be implemented in safety performance evaluation of a countermeasure without placing traffic at danger for an extended period. For instance, when there is apprehension about an adverse effect. Future research could investigate leveraging drivers’ behaviour to countermeasures, to improve the performance of collision-prediction regression models like the one proposed in this thesis. Finally, the results from the performance assessment of the LED active signs can assist transportation specialists in deciding whether or not to deploy these countermeasures.


identifier: Gabra, Mariam  (2022) Who Benefitted From the Covid-19 Pandemic?  Masters thesis, Concordia University.

abstract: Using different tests on different datasets, this paper empirically examines how healthcare firms and insiders used the Covid-19 pandemic opportunistically to raise capital and maximize their wealth. The research design consists of three parts. The first part examines biotechnology and Covid-19 related firms’ stock price to the onset on the pandemic using event studies and also examines long-term abnormal returns using the buy and hold abnormal returns (BHAR) approach. We find that the whole healthcare industry, and not just biomedical firms, produced high short-term and long-term abnormal returns. In the second part, we run an ordinary least squares regression and a two-way standard error clustered approach on the healthcare industry within Fama French 17 industries, propensity-matched score sample, and our own hand-collected dataset. Our results show that four industries within the healthcare industry capitalized on the opportunities provided by the pandemic; they are biomedical (SIC: 2836), pharmaceutical preparations firms (SIC: 2834), industrial organic chemicals and electromedical industry (SIC: 2860), and electrotherapeutic apparatus (SIC: 3845). The last section analyzes insider trading activities during three and four quarters before and after the pandemic. Using our collected sample firms and WHO Covid firms’ data, our results confirm that the purchases by insiders significantly increased during the first three quarters after the start of the pandemic. However, this does not last long, and we find strong selling in the fourth quarter after the start of the pandemic.


identifier: Wang, Kai  (2022) Novel Deep Learning Approaches for Single-Channel Speech Enhancement.  Masters thesis, Concordia University.

abstract:
Acquiring speech signal in real-world environment is always accompanied by various ambient noises, which results in the degraded intelligibility and quality of the speech. To make listeners hear the high-quality speech signal, speech enhancement is thus necessary, which aims to estimate the clean speech from noisy mixture by removing the background noises. Recently, deep-learning approaches, as a powerful tool, have impressively promoted the advancement of speech enhancement, which usually trains a neural network to learn the mapping function from the noisy speech to the clean speech with supervised learning. However, commonly used neural networks cannot efficiently leverage contextual information of speech signal while involving large footprint. For example, convolutional neural networks require to be deep enough for capturing sufficient receptive field due to the intrinsic locality. Besides, the recurrent neural networks cannot learn the long-term dependency of long speech sequences and moreover are computational-expensive because of the sequential processing.

To learn the contextual information of long-range speech sequencies, in the first contribution of this thesis, two novel attention-based transformer neural networks are proposed for single-channel speech enhancement: two-stage transformer and cross-parallel transformer neural networks, termed as TSTNN and CPTNN, respectively. The proposed TSTNN adopts multiple pairs of local and global transformer with cascaded connection to successively extract both local information of individual frames and global information across various frames, generating the contextual feature representation. To overcome the information leakage caused by shifting from one path to another in cascaded structure, the proposed CPTNN employs cross-parallel transformer blocks to extract local and global information in parallel, whose outputs are then adaptively fused by inner cross-attention mechanism for the generation of contextual information. Both proposed architectures incorporate the transformer blocks between convolutional encoder and decoder, where the outputs of transformer blocks are fed into a masking module to create a mask for filtering the encoder outputs which will be transformed to enhanced speech via decoder.  Extensive experiments indicate that the proposed TSTNN and CPTNN achieve a competitive or even superior performance compared to existing state-of-the-art methods in all evaluation metrics while having fewest trainable parameters.

While many competitive performances are realized by networks involving attention mechanism such as transformer as a part of them, it is worth-studying whether the attention is indispensable for resolving long-term dependency problem in speech enhancement, especially when considering the trade-off between computational efficiency and denoising performance. In the second contribution of this thesis, we propose an attention-free architecture based on multi-layer perceptrons (MLPs) for speech enhancement, named SE-Mixer, which consists of an encoder, a decoder and multiple mixer blocks in between. The mixer block is designed for efficiently extracting contextual information of long-range speech sequences. It employs temporal MLP in conjunction convolution and frequency MLP to iteratively capture multi-scale temporal information from various time scales and extract frequency information within each time step. Our experimental results demonstrate that the proposed SE-Mixer has a competitive performance and relatively low parameters compared to existing methods and without attention mechanism incorporated. We have also shown that the architecture without attention algorithm is likely to reach approximately the same effectiveness as compared with attention-assisted models but with significantly lower computational complexity.


identifier: Haiun, Adam  (2022) Spool.  Masters thesis, Concordia University.

title: Spool

abstract: Can we ever fully dislocate ideas of human-machine relations from either the anthropomorphized robot or the depersonalized computer console? Spool takes the form of a direct address, charting the devolution and ultimate breakdown of a relationship, delivered in initially regular packets of prose text which become increasingly afflicted by formal “malfunctions.” Its speaker is a living archive, leveraging a capacious bank of natural and unnatural images, scrambled into uncanniness by a machinic logic. Suffering the pangs of heartbreak, simulated or not, the speaker desperately weaves flailing links of non-meaning, seeking to shock, to seduce, to remonstrate, to implicate, to repay with pure strangeness the abuses of the reader. Though the speaker’s logic is absurd from the first poem, as though the cultivation of strangeness was encoded, accidentally or purposefully, as their primary function, there is a conscious movement from attempts at bridging a positive, if awkward, relationship between artificiality and the natural world, toward an emphasizing of their disparity, their incompatibility. At the same time, the speaker’s particular bank of images informs their machine nature; their references to anatomy, architecture, culture, all betray an unfamiliarity with embodied existence, and with a life which reaches beyond the confines of the digital. My principal task in working on this project was to invoke and curate a machinic voice, not by tinkering with software, but by calling attention to the paradoxically computer-like patterning of the unfiltered human thought process, exploring the boundaries of sanity and the mess of the interpersonal.


identifier: Riou, Geneviève  (2022) Remembering the Duvalier era: Resistance, Exile, and Solidarity in the Life Stories of Haitian-Montrealers.  Masters thesis, Concordia University.

abstract: From 2008 to 2012, Haitian survivors in Montreal were invited to share their memories of the Duvalier dictatorship for the oral history project the “Life Stories of Montrealers Displaced by War, Genocide, and other Human Rights Violations.” In their interviews, they recalled memories of life in Haiti before and during François Duvalier’s rule, as well as their experiences of exile after fleeing the country. In most cases, the stories they shared revolved around violence and the hardship they experienced after forced displacement. Other times, however, they recounted stories of resilience, resistance, and hope. This thesis explores this aspect of their life stories and asks how Haitian-Montrealers challenged the history of the Duvalier dictatorship in their interviews for the Montreal Life Stories project. As first wave Haitian exiles, some of these individuals took part in resistance against the Duvalier regime in Haiti, while others became involved in political and social causes after fleeing into exile. While their journeys as political activists varied, the ways in which they told their life stories as survivors shared striking similarities. In focusing on how they recounted their experiences of activism and exile in their interviews, as well as the reasons why they recounted them as they did, this thesis offers a more complete account of how Haitian-Montrealers remembered the Duvalier era for the Montreal Life Stories project. Additionally, it also explores the transnational connections and political solidarities they forged after fleeing Haiti, revealing the ways in which their lives and experiences have since extended beyond the legacy of the Duvalier regime.


identifier: St-Amant, Antoine  (2022) The Effects of Probiotics and the Low-Carbohydrate High-Protein Diet in Modulating Atherosclerosis.  Masters thesis, Concordia University.

abstract:
Atherosclerosis, a disease characterized by the accumulation of lipid-rich plaques in medium to large arteries, represents the most common cause of death in the world. Mitochondrial dysfunction contributes to many steps of the disease, through the production of reactive oxygen species (ROS) and by disrupting cell signalling pathways. Importantly, ROS induce the dedifferentiation of vascular smooth muscle cells, after which they migrate to the plaque region and proliferate, rendering the disease irreversible.

The western diet (W-DIET), rich in unhealthy fats and sugars, contributes to the epidemic of obesity and metabolic diseases, leading many individuals to alternative dietary patterns, including the low-carbohydrate high-protein diet (L-DIET). However, emerging evidence, both in humans and in animals, show that the L-DIET could worsen the progression of atherosclerosis, although the pathways through which the plaque buildup occurs remains largely unknown. In parallel, poor dietary patterns induce gut dysbiosis, which represents a major driver of diseases and strongly correlates with the development of cardiovascular pathologies. Hence, by restoring the integrity of the gut microbiota, probiotics supplements could prevent the buildup of atherosclerotic plaques.

Using a meta-analysis, high-resolution respirometry, immunoblotting, and polymerase chain reaction sequencing, this thesis explores the role of (1) supplements of probiotics and (2) the L-DIET in modulating oxidative stress, the mitochondria, and the gut bacterial composition. The data reported here present evidence that the L-DIET could induce mitochondrial dysfunction and gut-dysbiosis. The results also support that by improving mitochondrial integrity and biomarkers of oxidative stress, probiotics represent an affordable, low-risk alternative treatment in the prevention of atherosclerosis.


identifier: Carrese-Chacra, Emily, Hollett, Kayla, Erdem, Gizem, Miller, Sydney and Gouin, Jean-Philippe  (2022) Longitudinal Effects of Pandemic Stressors and Dyadic Coping on Relationship Satisfaction During the COVID-19 Pandemic.  Masters thesis, Concordia University.

creator:
Carrese-Chacra, Emily
Hollett, Kayla
Erdem, Gizem
Miller, Sydney
Gouin, Jean-Philippe

abstract: This study examined changes in relationship satisfaction during the COVID-19 pandemic and the moderating roles of financial strain, perceived threat of COVID-19, and dyadic coping. The Systemic-Transactional Model of Dyadic Coping posits that relationship satisfaction varies as a function of the stressors partners face and their engagement in dyadic coping. About 188 partnered adults completed questionnaires at three time points during the initial confinement period of the COVID-19 pandemic and at a 20-month follow-up. Relationship satisfaction increased during the first confinement period and returned to its baseline level at the 20-month follow-up. Greater financial strain and perceived threat of COVID-19 were associated with poorer relationship satisfaction over time. Dyadic coping buffered the negative impact of financial strain on relationship satisfaction during the initial confinement period, but not 20 months later. Most individuals were resilient to the effect of pandemic stressors on relationship satisfaction. The buffering effect of dyadic coping was observed during the initial confinement period when access to support resources outside the family unit was curtailed. Intervention efforts to promote dyadic coping and financial well-being for couples may be especially helpful in the context of strict confinement measures.