identifier: Lu, Lingfeng  (2021) An Exposition of Discrete Morse Theory and Applications.  Masters thesis, Concordia University.

abstract: The classical Morse theory is a powerful tool to study topological properties of a smooth manifold by examining critical points of some differentiable functions on that manifold. Robin Forman developed a discrete variant of Morse theory by adapting it on abstract simplicial complexes that resulted in a new theory with wide applications in other fields of mathematics, computer science, data science, and others. In this thesis, we present Forman’s construction of discrete Morse theory, as well as its main theorems such as the Collapse theorem, discrete Morse inequalities, the theorem for cancelling critical simplices, and some additional topics. We also discuss some applications of discrete Morse theory with a major focus on the concept of persistence in topological data analysis. While many results exist in the literature, we wrote our own proofs, added more details and explanations, and adapted it to our own settings with a strong topological flavor whenever possible.


identifier: Naaman, Karen  (2021) Three Essays on Say-on-Pay.  PhD thesis, Concordia University.

title: Three Essays on Say-on-Pay

type: Thesis NonPeerReviewed

abstract:
This dissertation comprises three essays on issues related to Say-on-Pay, a governance measure which allows shareholders to vote on executive compensation. In the first essay adopting a window-dressing perspective, I examine whether the mandatory adoption of Say-on-Pay is associated with opportunistic non-GAAP reporting to mislead shareholders about firm’s performance and avoid shareholder dissatisfaction against executive compensation. The sample comprises U.S. Fortune 250 firms, from 2003 until 2017. Results show that managers increasingly disclose non-GAAP earnings and exclude recurring items after the mandatory adoption of Say-on-Pay regulation. Also, managers’ exclusion choice of recurring items and the likelihood of reporting non-GAAP metrics are more pronounced during years when the firm is subject to a vote. The findings shed some light on the unintended consequences of Say-on-Pay, especially when the ethical concerns about non-GAAP reporting are raised.

The second essay integrates agency and resource dependence theories to examine the influence of compensation committee members’ qualities and non-GAAP reporting on shareholders’ Say-on-Pay support. Compensation committee quality is an aggregate measure of compensation committee attributes that include the directors’ interdependencies, their tenure, holding a CEO position, the number of seats they hold, and committee size. Results suggest that high quality compensation committees influence shareholders to provide a support to their Say-on-Pay vote. Moreover, the quality of non-GAAP reporting is associated with shareholders’ votes. Shareholders do not appear to be misled by low-quality non-GAAP metrics and managers’ opportunistic motive. On the contrary, shareholders vote against executive compensation when these metrics are of low-quality. While policy makers have set the regulation to curb excessive executive pay through shareholders’ votes, this study reveals that factors other than the excess pay itself may influence shareholders’ perceptions.

The third essay synthesizes research on Say-on-Pay and classifies it into two categories that revolve around the determinants and consequences of Say-on-Pay. Based on the first and second essays of my dissertation, I build a conceptual model that represents two closed interconnections. The first connection is between Say-on-Pay and compensation committees.
Shareholders’ Say-on-Pay votes are more favorable when compensation committee quality is high. However, when shareholders vote against executive compensation in Say-on-Pay, they also vote against the re-election of compensation committee members. The second connection of the model is between Say-on-Pay and non-GAAP reporting. The introduction of Say-on-Pay motivates managers to opportunistically report non-GAAP metrics. However, when managers report low-quality non-GAAP metrics, shareholders’ Say-on-Pay votes become more negative. Thus, it appears that Say-on-Pay holds simultaneously a dual role as both a determinant and a consequence in its relation to compensation committee and non-GAAP reporting.

Keywords: Say-on-Pay; Executive compensation; Non-GAAP earnings; Compensation committee quality; Interdependent directors; Director tenure; CEO directors; Director shareholdings; Additional directorships; Committee size.


identifier: AlFarajat, Eyad ORCID: https://orcid.org/0000-0002-1794-4644 <https://orcid.org/0000-0002-1794-4644>  (2021) Invariant Measures of Random Dynamical Systems with Constant Probabilities.  PhD thesis, Concordia University.

abstract:
In this PhD thesis we are concerned with the existence of the invariant measures and the absolutely continuous invariant measures under one-dimensional transformations. The thesis consists of two articles.
We establish the existence of invariant measures for random maps with constant probabilities and for nonautonomous random dynamical systems generalizing Krylov-Bogoliubov Theorem. We present results on the existence of an absolutely continuous invariant measure for the nonautonomous random maps on [a,b] using the theory of bounded variation.

We study the dynamics of a new family of transformations. We defined a general formula for the density function for any transformation belonging to our family, and we find some special properties for this family. This allowed us to study the random maps with constant probabilities based on these maps and to prove that the density function  f  of random map which is constructed from our family maps T= { τ1, τ2, ..., τn; p1, p2, ..., pn} is the combination  f = p1f1+ p2f2+ ...+ pnfn,  where  f1, f2, ...,  fn  are a density functions of  τ1, τ2, ..., τn respectively. We defined another family of transformations, and we proved that the density functions for any transformations belonging to this family are f(x)=1. We present an example to find the density function of the random maps by conjugations.

We created two classes of chaotic maps with desired invariant densities using two methods of solving the inverse Frobenius-Perron problem (IFPP). We studied the Lyapunov exponent and the autocorrelation properties for one of these classes.


identifier: Mohammadi, Behnam  (2021) Becoming a Gem: The Effects of Cultural Communication on the Transformation of a Rough Stone into a Gem.  Masters thesis, Concordia University.

abstract: For this thesis, I used practice-led research methods and storytelling to record and explain artwork development during studio practice. I demonstrate how, as an artist, my presence in a new place of residence influences my story. In addition, I have analyzed my reflections on my experiences from a research standpoint. From an artistic angle, I look at how a raw stone becomes an art object, and from a research perspective, I examine how knowledge is obtained and documented. I also explore the unspoken layers of making artwork and how the artist communicates his/her emotions while creating art. To ensure that practice-led research can be smoothly incorporated into an artistic activity, I accentuate the importance of striking a balance between intuition and organization within a creative project. Since I am also an artist (in addition to a researcher), I employ concept mapping in this approach in order to scrutinize how various elements are affected or influenced at each point of my study.


identifier: Zilembo, Giordano  (2021) A systematic approach for identifying fundamental successes and failures on complex product development programs.  Masters thesis, Concordia University.

abstract:
Organizations invest substantial resources to implement generic product development (PD) processes as a means to manage the development of high-complexity products. The difficulties reported on recent aircraft development programs suggest that manufacturers may not be fully benefiting from these tools. There is an opportunity for organizations developing complex products to learn from completed programs as a means to make informed improvements in their generic PD processes. Existing research supports that learning from projects in this way is mostly unsuccessful in industry. The lack of sophisticated project learning techniques capable of managing the complexity inherent to complex programs is a limiting factor to realizing this opportunity.

The purpose of this research project was to study an archived development program in order to extract useful information pertaining to the host organization’s PD process. A case study of an aircraft development program was undertaken to gain insight into the root causes of the program’s considerable schedule overrun. This included developing an approach for untangling the program’s non-intuitive behaviour and identifying the fundamental successes and failures of its execution. A mixed-methods research design incorporating quantitative and qualitative methods was developed and implemented. Additionally, an adapted thematic analysis (TA) method augmented with elements of qualitative content analysis (QCA), thematic networks (TNs), and causal maps was formulated for this investigation.

The results of the case study included a tiered catalogue of root causes driving the program’s outcome and a map of their causal linkages. These themes are uncovered lessons pertaining to the host organizations PD process and the fundamental successes and failures of its actual execution. These results are of value to the host organization and empower it to make informed improvements in its processes. They are also insightful for any organization undertaking complex PD. The overarching result of this study is ultimately the research design itself as an effective mechanism for systematically identifying the root causes of a complex development program’s outcome and untangling their interactions. This result is an explicit contribution to the need for more sophisticated organizational project learning mechanisms specifically applicable to complex programs. Moreover, it is an enabler to developing a full-fledged process for making closed-loop improvements to PD processes as a means to achieve their ongoing improvement.


identifier: Torabinejad, Elnaz  (2021) Kinematic Analysis of Postural Anticipation and Recovery in Young and Older Adults.  Masters thesis, Concordia University.

abstract:
The maintenance of balance is one of the most important capabilities of humans. This ability is more crucial for older adults considering that over one in four elderly adults experience at least one fall (Bergen et al., 2016a) Empirical evidence showed that working memory plays role in maintaining balance. Working memory degrades by increased age. In the present study, the Dual Mechanisms of Control framework ( Braver, 2012), was utilized to evaluate the role of working memory in maintaining balance in older and younger adults. Participants were presented with visual cues indicating if the platform beneath them was likely (A) or unlikely (B) to move. On 70% of trials, cue A was followed by a forward horizontal translation of the platform. On 10% of trials, the B cue was followed by a platform movement (invalid trials). The remaining non-movement trials were either valid (B cue, 10%) or invalid (A cue, 10%) and not analyzed. Retention of goal-relevant cue information in working memory is thought to decline with aging. Kinematic signals (hip, knee, ankle joint angles) were captured by a Vicon system and characterized as (i) peak amplitude, (ii) peak latency and (iii) recovery deviation, were analyzed as a function of age group (young, older), cue type (A: likely platform movement; B: unlikely movement), and testing stage (early Block 1; late Block 6). To address the anticipated age differences in proactive control, an additional factor was considered using a neuropsychological test of working memory capacity.
Together, these four factors were included in a series of MANOVAs, using the three kinematic parameters for each of the three joint angle data. The results of multivariate ANOVAs suggested that the there was a significant effect of age and level of working memory in different age groups in some joint angles.
Furthermore, using methods of machine learning, the prediction of age group based on the kinematic characteristics was applied. Each measurement was considered as a feature and due to the excess number of features, feature selection methods (PLS, PCA, Correspondence Analysis)  were applied on the dataset. The selected features by each method, composed new datasets. Three different method of Machine Learning (Decision Tree, Random Forest and Naïve Bayes) were applied to the datasets with 10-fold cross-validation. The best accuracy (0.83) was achieved by applying the Decision Tree method on a dataset selected with Partial Least Square (PLS) method. Together these results supports the Dual Mechanism of Control framework  and suggests that working memory is used to maintain balance, and older adults utilized cues differently than younger adults.


identifier: Abtahi, Seyed Matin  (2021) Control-Oriented Thermal Network Models for Predictive Load Management in Canadian Houses with On-Site Solar Electricity Generation: Application to a Research House.  Masters thesis, Concordia University.

abstract:
This study presents a methodology to develop suitable control-oriented thermal RC network models for optimized HVAC load management in typical electrically heated single-family detached houses. Using recurring parameter identification and model-reset, the building dynamics are represented by an explicit discrete time-varying state-space formulation.
Next, these models are applied in a predictive control framework in which the objective is to enhance energy efficiency and energy flexibility of the building by prioritizing the import from the most efficient energy source(s), storing energy in the building's thermal mass and/or a battery, and shifting the HVAC load to lower the stress on the local grid.
Finally, the benefits of predictive control strategies for HVAC load management, both for the building owners and the local grid, are studied through a seasonal simulation where the performance of the building subject to a reference reactive controller and a predictive controller are compared. Applying the predictive controller, the results show an average of 12.1% reduction in the daily heating load, 19.8% reduction in the total daily import, 68.1% reduction in the peak demand, 67.0% reduction in the daily energy cost, and 13.4% increase in the self-consumption of on-site generated solar electricity for the duration of January 1st to March 31st (90 days), compared to the reactive controller.


identifier: Matthews, Tomas  (2021) Finding Groove in Behaviour and the Brain.  PhD thesis, Concordia University.

abstract:
Movement, perception, and reward are fundamental processes underlying much of our behaviour which, although separable, are strongly linked. For example, moving to music requires the extraction of timing information from auditory input to synchronize movements to musical rhythms, a process that often leads to pleasure. But why does it feel good to move to music, and what aspects of the music make us want to move? Further, what are the brain networks underlying this urge to move? One approach to answering these questions is to study the sensation of groove, which is defined as the pleasurable urge to move to music. The work presented in this thesis investigated groove using behavioural and neuroimaging methods to shed new light on music’s ability to move us and the fundamental processes that support this phenomenon.
	Groove has been shown to be strongly influenced by rhythm, however, other aspects of music are likely to contribute. Article 1 investigated the role of harmonic complexity, showing that it interacts with rhythmic complexity in determining groove. A mediation analysis showed that harmonic complexity affects groove primarily via its impact on pleasure.
	There is some evidence that moving to music increases groove. However, it is unclear if this depends on whether listeners feel as though they are synchronizing accurately. Article 2 compared the relative impact of perceived and measured synchrony on groove. Perceived synchrony showed a stronger relation with groove indicating that ‘feeling in sync’ is a crucial driver of groove.
	Separate lines of research have investigated the brain networks involved in rhythm perception and music-induced pleasure. Groove provides the opportunity to investigate these processes together. Article 3 investigated the brain regions underlying groove using functional magnetic resonance imaging. Groove elicited activation in motor timing and reward networks with the basal ganglia implicated in both.
	Together, these studies provide novel insight into groove and its underlying processes. These results are discussed in the context of the integration of predictive coding and dynamic attending treatments of rhythm perception and groove. I suggest that predictive timing processes form the foundation on which groove is built.


identifier: Al-Hilo, Ahmed Mahdi Abed  (2021) Towards Smart Vehicular Environments via Deep Learning and Emerging Technologies.  PhD thesis, Concordia University.

abstract:
Intelligent Transportation Systems (ITS) embrace smart vehicular environments through a fully connected paradigm known as vehicular networks. Vehicular networks allow automobiles to stay online and connected with their surroundings while travelling. In that sense, vehicular networks enable various activities; for example, autonomous driving, road surveillance, data collection, content delivery, and many others. This leads to more efficient, safer, and comfort driving experiences and opens up new opportunities for many business sectors. As such, the networking industry and academia have shown great interests in advancing vehicular networks and leveraging relevant services.

In this dissertation, several vehicular network problems are addressed along with proposing novel ideas and utilizing effective solutions. As opposed to stationary or slow moving communications, vehicular networks experience more challenging environment as a result of vehicle mobility. Consequently, vehicular networks suffer from ever-changing topology, short contact times, and intractable propagation environments. In particular, this dissertation presents six works that participate in supplementing the literature as follows. First, a content delivery framework in the context of vehicular network is studied where digital contents are generated by different content providers (CP) and have distinct values. To this end, a prefetching technique along with vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communications are used to enable fast content delivery. Furthermore, a pricing model is proposed to deal with contents' values to attain a satisfactory Quality of Experience (QoE). Second, a more advanced system model is discussed to cache contents with the assistance of vehicles and to enable a disconnected and fixed Road-Side Unit (RSU) to participate in providing content delivery services. The changing popularity of contents is investigated besides accounting for the limited RSU cache capabilities. Third, the stationary RSU proposed in the second work is replaced by a more flexible infrastructure, namely an aerial RSU mounted on an unmanned aerial vehicle (UAV). The mobility of the UAV and its constrained energy capacity are analyzed and Deep Reinforcement Learning is incorporated to aid in solving the challenges in leveraging UAVs. Fourth, the previous two studies are integrated by investigating the collaboration between a UAV and terrestrial RSUs in delivering large-size contents. A strategy to fill up the UAV cache is also suggested via mulling contents over vehicles. Fifth, the complexity of vehicular urban environments is addressed. In particular, the problem of disconnected areas in vehicular environments due to the appearance of high-rise buildings and other obstacles is studied. In details, a Reconfigurable Intelligent Surface (RIS) is exploited to provide indirect links between the RSU and vehicles travelling through such areas. Our sixth and final contribution deals with time-constrained Internet of Things (IoT) devices (IoTD) supporting ITS networks. In this regard, a UAV is dispatched to collect their data timely and fully while being assisted by a RIS to improve the wireless channel quality. In the end, this dissertation provides discussions that highlight open research directions worth of further investigations.


identifier: Gritli, Nour  (2021) An Automated Approach for Network Slice Design from Tenant Intents.  Masters thesis, Concordia University.

abstract:
With the emergence of 5G, multiple vertical industries are seeking to leverage new type of services with stringent and diverse performance requirements. Monolithic network architectures do not allow for supporting efficiently such services at the same time. In this context, the network slicing paradigm was introduced to enable network operators to create multiple end-to-end logical networks, i.e. network slices (NwSs), on top of a common and shared physical infrastructure. Each NwS is customized to meet specific functional and non-functional requirements such as Quality of Services (QoS) and isolation requirements.
Intent-based networking is considered as one of the key paradigms to automate and reduce the complexity of managing multiple network slices with divergent requirements. An intent-based networking system should allow for expressing requirements, at a high level of abstraction without low level networking/resource details, and be able to translate these requirements into low-level and deployment related information. Applying the intent-based networking paradigm in the network slicing context will allow for the automation of its provisioning process starting from the preparation phase to the runtime phase.
In this thesis, we propose a model-driven approach to automate NwS design from tenant intents. The proposed approach consists of several steps and starts from intents expressed by the tenant (NSliceReq) and intents expressed by the operator. The NSliceReq expresses high-level requirements for communication services (CSs) and NwSs along with their non-functional required characteristics. The operator intents describe the slice types supported by the operator from a QoS perspective. The proposed approach starts by combining both intents in a consistent manner and identifying the NwSs to design and their characteristics as a set of combined intents solutions. In the next step, with the help of an ontology, the approach processes and decomposes each combined intents solution. This decomposition allows for enriching and propagating the isolation intents expressed, in the NSliceReq, for the NwS or its supported CSs. In order to select the appropriate VNFs and PNFs to compose the NwS, we start by assigning the placement constraints of the composing NFs of the required NwSs/CSs. To achieve this we take into consideration, during the design process, placement constraints originating from different sources, namely the tenant, the operator, the available VNFs/PNFs and the standards. The VNF and the PNFs are selected based on the decomposition information and the assigned placement constraints. Thereafter, the approach generates the forwarding graphs, the traffic flows and dimensions the selected VNFs/PNFs. In the following step, the approach performs the embedding of each forwarding graph according the QoS intents. We then use the embedding information as well as the management constraints to determine the NwSSs and the realizing NS(s) of the required NwSSs. NwSTs and NSDs are then generated according to this mapping. The proposed approach automates the NwS design process and a prototype tool has been implemented as a proof-of-concept. This prototype consists of a set of model-based transformations representing the different steps of the approach. We demonstrate the prototype using a NSliceReq comprising an intent for an enhanced Mobile Broadband (eMBB) NwS and an intent for a remote gaming application.


identifier: Yu, Yazhuo  (2021) The relationship between the use of derivatives and firm value under different economic cycles.  Masters thesis, Concordia University.

abstract: This thesis explores the effect of derivative usage for hedging on firm value. By using a quarterly dataset of North American firms from 2000 to 2017, I examine whether the use of derivatives for hedging adds firm value. I focus on derivatives used for hedging rather than the generalized use of derivatives. Hedging can be an effective method of risk management and active risk management can lead to an increase in firm value. Firms are classified as ineffective speculators (IS firms) and effective hedgers (EH firms) based on their risk exposures before and after the use of derivatives. I add the economic cycles as another factor that might affect the effect of hedging on firm value. The results indicate that the use of derivatives for hedging adds firm value and the effect can last for longer than one year. For smaller firms, the value increase arising from hedging is more significant than that for larger firms. During economic expansions, hedging adds more value than that during economic recessions.


identifier: Dodds, Matthew  (2021) Uncertain Conspiracies: A Latourian Analysis of R/Conspiracy in an Era of Global Upheaval.  Masters thesis, Concordia University.

abstract: In the 21st century, digital tools have made it possible to disseminate information across physical boundaries instantaneously. This, combined with an increasingly polarized and uncertain climate in world affairs, has allowed ideologies of conspiracy to find receptive audiences across the globe. R/conspiracy, a popular forum where many congregate to with like-minded individuals provides a dynamic and rich research site to study the language and discourse taking place under a broad conceptualization of conspiracy. Using theoretical tools created by Bruno Latour (2005), this paper analyzes r/conspiracy over a period of 4 days to demonstrate the inadequate understanding of the conspiracist community elucidated by present day academics.


identifier: Patel, Shivam Dimplekumar  (2021) Augmenting Network Performance Datasets with Weather, Sports, and Social Media Data for Improved Predictions.  Masters thesis, Concordia University.

abstract:
Understanding network performance enables network providers to manage their network
better. Network performance degradation can lead to network service issues causing monetary
loss and customer churn for the network providers. Accurate network performance
prediction potentially enables proactive resource allocation to attenuate the anticipated network
performance degradation and associated service issues. Previous literature attempted
to predict network performance using historical network data. However, real-world network
performance is impacted by various external factors. Existing literature fails to consider
such external factors that can improve the understanding and predictions of the network
performance. This thesis aims to examine if external factors can improve the network
performance understanding and predictions. To this end, we inspect the correlation of
network performance data with various external data sources such as weather parameters,
sports events, and social media posts. Then, we perform network performance data augmentation
using the contextual information in such external data. We investigate the network
performance prediction improvements using Recurrent Neural Network (RNN) with
Long Short Term Memory (LSTM) units after data augmentation. Predictive experiments
with data augmentation using NFL sports events highlight a 23% improvement in the network
performance predictions. Data augmentation using other external sources considered
fails to improve the network performance predictions.


identifier: Gagné, Jean-Philippe ORCID: https://orcid.org/0000-0001-5803-0489 <https://orcid.org/0000-0001-5803-0489>  (2021) Psychometric and Experimental Investigations of Beliefs About Losing Control.  PhD thesis, Concordia University.

abstract: According to cognitive theory, maladaptive beliefs play a pivotal role in the development and maintenance of anxiety-related problems and there is overlap in the beliefs involved across these disorders. Interestingly, clinical reports claim that individuals with obsessive-compulsive disorder (OCD) and with social anxiety disorder (SAD) fear losing control over their thoughts, behaviour, emotions, and/or bodily functions. This indicates that negative beliefs about the likelihood and consequences of losing control could be involved in both disorders. This program of research was designed to foster psychometric investigations of beliefs about losing control and increase our understanding of the causal role of these beliefs in OCD and SAD. In Study 1, a measure of maladaptive beliefs about losing control, the Beliefs About Losing Control Inventory (BALCI), was validated in a sample of undergraduate students (N = 488). Results indicated that the BALCI’s items capture beliefs about losing control over one’s thoughts/behaviour/emotions (Factor 1), about the importance of staying in control (Factor 2), and about losing control over one’s body/bodily functions (Factor 3). The BALCI was found to be psychometrically sound and associated with OCD symptoms above and beyond already established maladaptive beliefs. In Study 2, beliefs about the likelihood of losing control over one’s behaviour were manipulated by providing false feedback to undergraduate participants (N = 128). Believing that one is likely to lose control over their behaviour led to increasing anxiety while approaching stimuli that are typically feared in OCD, lower perceived caution while interacting with these stimuli, and recalling experiencing more unwanted intrusions throughout the protocol. In Study 3, beliefs about the likelihood and consequences of losing control over one’s actions/speech were manipulated by assigning undergraduate participants (N = 93) to drinking vodka (alcohol condition), alcohol-free vodka (placebo condition), or orange juice (control condition). Participants then interacted with a stranger. Results indicated that those in the placebo (versus control) condition experienced greater anxiety, perceived themselves as making a poorer first impression, and reported engaging in more post-event processing. The pharmacological effects of alcohol appeared to mitigate the effects of beliefs about losing control. Implications for cognitive-behavioural theories and therapies are discussed.


identifier: Jandaly, Anita  (2021) The Ideologies of Dyadic Friendships: A Text Analysis and Children’s Reading of “Buzz” and “Woody” From Disney-Pixar’s Toy Story Films.  Masters thesis, Concordia University.

abstract: Disney-Pixar’s animated films are found to offer ideological lessons to audiences; however, limited research exists on the ideologies of friendships that the films promote. This qualitative study combines cultural studies with a critical media literacy (CML) framework to examine one film text, specifically how dyadic friendships are depicted through the characters of “Buzz” and “Woody” in Disney-Pixar’s Toy Story films, and explores how Toy Story can be used as a CML tool to discuss friendships with children. Using a text analysis to examine the ideologies of Buzz and Woody’s friendship, five themes emerged: friendship formation is influenced by (1) internal, (2) external, and (3) interpersonal factors; (4) maintained by affective reciprocity; and (5) face a fate of friendship. An audience reading included two girls and one boy (13 years of age) of ethnically diverse backgrounds, from Canada (N = 2) and the United States (N = 1). Participants were interviewed individually and asked about their perceptions of Disney and friendship. Participants then participated in a focus group interview and collectively watched five purposefully chosen excerpts of Buzz and Woody from the series; they were asked open- ended questions informed by elements of CML about their perceptions of friendship after each scene. Four findings emerged on children’s conceptualizations of Buzz and Woody’s friendship: (1) a gradual progression from enemies to close friends, (2) comprised of reciprocal efforts, (3) a context to negotiate identity and ambitions, and (4) an unknown fate and future. This study concludes with Toy Story’s potential as a pedagogy of friendship.


identifier: Ferraro, Sarah  (2021) Effects of Prenatal Administration of Valproic Acid on Circadian Organization and Clock-Gene Expression: Implication for Autism Spectrum Disorders.  PhD thesis, Concordia University.

abstract:
Autism Spectrum Disorder (ASD) is a significant lifelong neurodevelopmental disorder characterized by alterations in social-emotional communication and the presence of restrictive and repetitive behaviours. Circadian rhythm disruption is one of the most common comorbidities in ASD, affecting up to 80% of individuals. However, despite the increasing prevalence of the disorder over the past decade, insights into the nature of circadian rhythm disruption in the disorder remain poorly investigated and understood.

This objective of this thesis was to characterize the circadian system in a valproic acid (VPA)-induced rodent model of ASD. First, we examined wheel-running behaviour – the current gold standard for describing functional changes within the circadian system – in both male and female Wistar rats exposed to either saline or VPA in utero. We demonstrated the existence of a diminished and unstable master clock in VPA-exposed animals in which aberrant behaviour was driven by alterations in photic-entrainment capacity. Secondly, we investigated the daily expression profile of BMAL1, a core clock-gene necessary for circadian behaviour, in neural structures involved in the pathogenesis of ASD behaviours. Here, we showed altered temporal dynamics of BMAL1 in peripheral tissues involved in the regulation of social behaviours, motivation, reward and monoaminergic output and suggested a potential role for the clock in the emergence of maladaptive behaviours seen in ASD. Finally, we showed that the emergence of circadian disturbances post in utero exposure to VPA can be passed onto the second and third generations, opening the possibility that circadian rhythm disruption can be passed onto future generations through the germline. Collectively, this body of research emphasizes the urgent need for novel perspectives in the treatment of ASD-associated comorbidities and highlights the nature of circadian dysregulation in the disorder.


identifier: Pittman, William  (2021) A Qualitative Content Analysis of Quebec Suicide Notes.  Masters thesis, Concordia University.

abstract: This paper will present the results of a qualitative content analysis of 292 Québec suicide notes from the year 2005. The content of suicide notes differed based on age and sex; experiencing a recent breakup also affected the content of the notes. The sociological significance of the results is explored in an effort to gain insight into contemporary trends in Western suicide, most notably the prevalence of youth suicide and the over-mortality of males. Suicide notes from teens and young adults contained the most instances of complaints about society, which may indicate a level of disdain for the world they are leaving behind. In addition, youth suicide notes were characterized by a lack of precise meaning attached to their actions, which indicates either an inability to define their situation, or an unwillingness to do so. Suicide notes from females contained more soothing remarks as well as more remarks denoting vengeance or anger towards others; this is interpreted as a tendency to focus on interpersonal elements when framing their message. Males, conversely, focused more on their internal characteristics when framing themselves and their situation within the notes. For males experiencing a recent breakup, their tendency was to frame themselves as dejected and deserving of their fate; for females experiencing a recent breakup, their tendency was to frame themselves as a victim of harmful individuals. Regardless of gender, the presence of a breakup drastically changed the collective message of the suicide notes.


identifier: Hou, Lianze  (2021) The Effects of Bitter Taste on Consumer Behaviour.  Masters thesis, Concordia University.

abstract: Bitter taste is innately aversive. The association between bitterness and difficult situations have been widely documented across various disciplines. A set of psychological adaptations may have co-evolved with the physiological responses to bitter taste, in responding to the recurrent challenge of harsh environments in human evolutionary history. Bitter taste is proposed to activate psychological mechanisms evolved for obtaining and retaining resources. In connection with consumer behaviour, experiencing bitter taste may alter consumers’ preference toward high-calorie food and body-enhancing products. In this thesis, three experimental studies demonstrate how bitter taste influences consumers’ behaviours. Study 1 finds that Chinese participants who drink bitter quinine-sulfate water solution consume significantly more high-calorie food, compared to those who drink plain water. Study 2 and 3 show that, in the Canadian cultural context, participants who imagine drinking a bitter beverage report higher competitive orientation and weigh the body-enhancing product attributes more in the choice task, compared to those who are primed with drinking plain water. This thesis contributes to introducing Darwinian principles to sensory marketing and adds to the existing literature on the effects of bitter taste on consumer behavior. Furthermore, it provides managerial implications for policy makers and marketing managers regarding how to promote healthy diets and how to improve the effectiveness of marketing campaigns for self-enhancing products.


identifier: Donnarumma, Pedro Rafael ORCID: https://orcid.org/0000-0002-5166-956X <https://orcid.org/0000-0002-5166-956X>  (2021) Synthesis, Optimisation, and Characterisation of Rare-earth Analogues of UiO-66.  Masters thesis, Concordia University.

abstract:
This work explores a particular sub-field of metal–organic frameworks (MOFs) incorporating rare-earth (RE) metals, also called RE-MOFs, that have been gaining traction over the last 30 years. The specific family studied here, analogues of the archetypical UiO-66, incorporates RE(III)-hexanuclear clusters and linear organic linkers, giving rise to a network with fcu topology named RE-UiO-66. Herein, the following is presented (i) the design, synthesis, and characterisation of the RE-UiO-66 (RE = Y(III), Eu(III), Gd(III), Tb(III), Ho(III), Er(III), Tm(III), and Yb(III)); (ii) the challenges and optimised approaches for the synthesis of each RE-UiO-66 analogue; (iii) the crystalline structure of the entire family of RE-UiO-66 analogues, through the use of single crystal X-ray diffraction (SCXRD); and (iv) the challenges associated with synthesising early lanthanoid analogues of RE-UiO-66 (RE = La(III), Ce(III), Pr(III), and Nd(III)).
Chapter 2 delves into the synthetic optimisation, and characterisation of a series of RE(III) analogues of Zr(IV)-UiO-66. RE-UiO-66 shows several similarities to Zr-UiO-66, a well-studied MOF in the literature; but the post-activation stability of the former is not similar to the latter one, requiring further optimisation. The physical and chemical properties of RE-UiO-66 and some stabilisation pathways, as well as the crystal structure of Tm-UiO-66, are discussed further.
Chapter 3 aims to explain trends in bond lengths observed in the crystal structures of RE-UiO-66 (RE = Y(III), Eu(III), Gd(III), Tb(III), Ho(III), Er(III), Tm(III), and Yb(III)). These trends are then used to explain some of the physical and chemical properties of the RE-UiO-66 series as described in Chapter 2. By using acidic conditions and high temperatures, single crystals suitable for SCXRD are obtained. From this data, the structure of each RE-UiO-66 analogue was solved and refined.


identifier: Norouzi, Shahrzad ORCID: https://orcid.org/0000-0002-9185-847X <https://orcid.org/0000-0002-9185-847X>  (2020) Flow Characteristics in Abdominal Aortic Aneurysms: An in vitro Study.  Masters thesis, Concordia University.

abstract:
An abdominal aortic aneurysm (AAA)  is a vascular disorder that emerges when the aortic wall degenerates and the abdominal aorta undergoes a permanent expansion of at least 1.5 times its normal diameter. If an AAA is left undiagnosed and untreated, it can eventually rupture with an associated mortality risk of 81%. Clinically, a maximum diameter exceeding 5 cm is considered the decisive criterion to identify at-risk AAAs. The present work investigates the flow dynamic variations associated with aneurysm experimentally, using compliant AAA models and time-resolved particle image velocimetry (TR-PIV). For this purpose, an in vitro setup is designed and developed to simulate the flow inside 6 idealized phantoms mimicking in vivo physiological properties. The instantaneous flow fields in two orthogonal planes reveal that the flow behavior in the early stages of an aneurysm does not deviate significantly from that of the healthy aorta. An increase in the size and number of bulges triggered the evolution of features such as flow detachment, swirling motion, wall impingement and the collapse of the vortical structures within the aneurysm sac. All these characteristics are more noticeable in the AAA model with a maximal diameter equal to the clinical threshold. Therefore, in the context of fluid dynamics, this perception can provide physical support to the Dmax=5 cm criterion to nominate an AAA patient for elective surgery. It is assumed that the onset and propagation of large vortical structures in the deceleration phase and the formation of stagnant flow regions near the proximal neck of the largest model can lead to unfavorable hemodynamic changes that escalate the weakening, enlargement and rupture of the aortic wall.
Following recent applications of viscous energy dissipation in the severity stratification of cardiovascular diseases, as part of this thesis, the associated energy loss is quantified in order to examine its correlation with changes in the geometry and flow topology of each model. Although the two largest models were identified with the highest energy losses, which can be attributed to their higher shear stresses, this parameter does not follow a clear increase with the aneurysm expansion. In the other four cases, the kinetic energy was almost equally well preserved. The experimental AAA flow data in this work is also inspected from a modal analysis perspective, in particular proper orthogonal decomposition (POD), to identify and extract the dominant structures, which can provide more insights on the disease progression. The Shannon (global) entropy demonstrates that as the aneurysm expands, the modal energy distribution becomes dispersed, meaning that more modes are required to describe and model the flow. This parameter, in turn, can potentially be applied in clinical assessment of the severity of patient-specific AAAs.


identifier: Basnet, Bigyan  (2021) Modeling, Analysis and Control of a Variable Flux Machine.  PhD thesis, Concordia University.

abstract:
Electric motors are the key elements in electric propulsion systems. The performance of Electric vehicles (EVs) significantly depends on the electric motors. Permanent magnet synchronous machines (PMSMs) with rare-earth magnets are widely used in EV applications because they fulfill most requirements of EV motors. However, low efficiency at high speed, limited resources and fluctuating prices of rare-earth permanent magnets (PMs) have forced industries to develop alternatives to rare-earth machine technologies. Recently, Variable-Flux PMSMs (VF-PMSMs) also known as memory motors have been introduced to overcome the drawbacks of PMSMs. This thesis focuses on the modeling, analysis and control of the Aluminum-Nickel-Cobalt (AlNiCo) magnet-based VF-PMSMs.
This thesis presents the effect of different magnetization pulse widths and methods on the magnetization level, back-EMF and no-load losses of the VF-PMSM. The injection of the magnetization or de-magnetization current pulse will change the magnet flux linkage and back-EMF harmonics. An adaptive nonlinear filter is used to estimate the back-EMF during the motoring mode. The harmonics present in the machine back-EMF due to different magnetization and de-magnetization current pulse widths and magnetization methods are analyzed. Besides, the quality of the back-EMF for different speeds and machine no-load losses are presented for different magnetization states (MSs).


identifier: ElSheikh, Muhammad  (2021) MILP-aided Cryptanalysis of Some Block Ciphers.  PhD thesis, Concordia University.

abstract:
Symmetric-key cryptographic primitives, such as block ciphers, play a pivotal role in achieving confidentiality, integrity, and authentication – which are the core services of information security. Since symmetric-key primitives do not rely on well-defined hard mathematical problems, unlike public-key primitives, there are no formal mathematical proofs for the security of symmetric-key primitives. Consequently, their security is guaranteed only by measuring their immunity against a set of predefined cryptanalysis techniques, e.g., differential, linear, impossible differential, and integral cryptanalysis.

The attacks based on cryptanalysis techniques usually include searching in an exponential space of patterns, and for a long time, cryptanalysts have performed this task manually. As a result, it has been hard, time-consuming, and an error-prone task. Indeed, the need for automatic tools becomes more pressing. This thesis is dedicated to investigating the security of symmetric-key cryptographic primitives, precisely block ciphers. One of our main goals is to utilize Mixed Integer Linear Programming (MILP) to automate the evaluation and the validation of block cipher security against a wide range of cryptanalysis techniques. Our contributions can be summarized as follows.

First, we investigate the security of two recently proposed block ciphers, CRAFT and SPARX-128/256 against two variants of differential cryptanalysis. We utilize the simple key schedule of CRAFT to construct several repeatable 2-round related-key differential characteristics with the maximum differential probability. Consequently, we are able to mount a practical key recovery attack on full-round CRAFT in the related-key setting. In addition, we use impossible differential cryptanalysis to assess SPARX-128/256 that is provable secure against single-trail differential and linear cryptanalysis. As a result, we can attack 24 rounds similar to the internal attack presented by the designers. However, our attack is better than the integral attack regarding the time and memory complexities.

Next, we tackle the limitation of the current Mixed Integer Linear Programming (MILP) model to automate the search for differential distinguishers through modular additions. The current model assumes that the inputs to the modular addition and the consecutive rounds are independent. However, we show that this assumption does not necessarily hold and the current model might lead to invalid attacks. Accordingly, we propose a more accurate MILP model that takes into account the dependency between consecutive modular additions. As a proof of the validity and efficiency of our model, we use it to analyze the security of Bel-T cipher—the standard of the Republic of Belarus.

Afterwards, we shift focus to another equally important cryptanalysis technique, i.e., integral cryptanalysis using the bit-based division property (BDP). We present MILP models to automate the search for the BDP through modular additions with a constant and modular subtractions. Consequently, we assess the security of Bel-T block cipher against the integral attacks. Next, we analyze the security of the tweakable block cipher T-TWINE. We present key recovery attacks on 27 and 28 rounds of T-TWINE-80 and T-TWINE-128, respectively.

Finally, we address the limitation of the current MILP model for the propagation of the bit-based division property through large non-bit-permutation linear layers. The current models are either inaccurate, which might lead to missing some balanced bits, or inefficient in terms of the number of constraints. As a proof of the effectiveness of our approach, we improve the previous 3- and 4-round integral distinguishers of the Russian encryption standard—Kuznyechik, and the 4-round one of PHOTON’s internal permutation (P288). We also report a 4-round integral distinguisher for the Ukrainian standard Kalyna and a 5-round integral distinguisher for PHOTON’s internal permutation (P288).


identifier: Laframboise, Lauren  (2021) Gendered labour, immigration, and deindustrialization in Montreal's garment industry.  Masters thesis, Concordia University.

abstract: For nearly a century, the garment industry was a driving force of Montreal’s economy, and a major employer in the city’s manufacturing industries. However, the Canadian government pursued a progressive trade liberalization policy in the 1970s, and the effects of increased import competition led to successive waves of closures in the domestic textile and clothing industries. Due to the historically entrenched gender norms that structured the Canadian garment industry, immigrant women workers were often the first to be laid off, bearing the brunt of restructuring. These closures occurred against the backdrop of a profound crisis in the industry’s institutions, increased labour intensification, and rapidly deteriorating working conditions. Tensions culminated in the 1983 garment strike, when rank and file workers organized against job losses and widespread de-unionization. Organizers drew on the language and politics of the women’s movement in Quebec to highlight the historic marginalization of women in garment manufacturing, and to articulate their resistance to deindustrialization. However, this study also aims to de-center wage labour within our understandings of life under capitalism, showing that women’s experiences of deindustrialization were also shaped by their unpaid reproductive labour within the home. The impacts of paid and unpaid labour combined often left workers with poor health outcomes, revealing the longer-term, “slow violence” of capitalism. Through oral history interviews with former garment workers, rank and file organizers, union officials and employers, I show that deindustrialization in Montreal’s garment industry was a highly gendered process, and that its effects were felt at the intersection of existing marginalities.


identifier: Simunic, Emily  (2021) Problematizing Canadian Human Trafficking Policy.  Masters thesis, Concordia University.

abstract: This thesis seeks to determine how human trafficking is problematized in Canadian policy and what subsequent effects are produced by this problem representation in the lived experience of political subjects in Canada. Using Carol Bacchi’s “What’s the problem represented to be?” poststructural analytic strategy to Canadian policy texts, I demonstrate that human trafficking is represented as a “criminality problem” in Canadian policy texts. The criminality problematization represents the “problem” of human trafficking to be crime requiring state intervention in the form of enforcement and punishment through fees and incarceration. The criminality problematization is predominantly interested in women as potential victims of sex trafficking, and emphasizes strategies to safeguard women from predominantly male violence. Chapters three and four perform Foucauldian archaeology and genealogy, troubling the assumptions which undergird the problematization and revealing the impact of white slavery as a discursive precedent to human trafficking. Chapter five identifies the discursive, subjectification and lived effects of the problematization, revealing that the criminality problematization has served only to reinforce preexisting inequalities, oppressions, and vulnerabilities that create the conditions that lead to human trafficking in the first place. I conclude that the criminality problematization of human trafficking cannot yield socially just policy, and I suggest the  “inequality problematization,” as an alternative problem representation that considers human trafficking to be a “problem” rooted in, and exacerbated by, inequality.


identifier: Roy, Shannon  (2021) The Truth of What Matters: An Autoethnography and Visual Inquiry of Art Teacher Burnout.  Masters thesis, Concordia University.

abstract: Teachers have long struggled with stress and burnout due to the job’s physical, mental, and emotional complexities. This autoethnography explores teacher stress and burnout through six social fiction short stories and accompanying photographs. My personal accounts of teaching art inform the discussion around why so many teachers are experiencing burnout and why art teachers struggle to maintain an artistic practice while teaching. To understand more precisely the issues that teachers are facing, I have identified four prevalent challenges for art teachers. These issues are insufficient teacher preparation, lack of teacher support, excessive workload, and breakdown of identity. Additionally, a fifth theme, “connection” emerged as a positive intervention. This thesis also explores how connections to the school community and staff, students, and through engagement with an active art practice are beneficial to an art teacher’s well-being.


identifier: Borenstein-Laurie, James  (2021) Examining Intra- and Inter-Personal Health Effects of Optimism and Pessimism: The Role of Subjective Well-Being in Romantic Couples.  Masters thesis, Concordia University.

abstract: Recent meta-analytic research suggests that the absence of pessimism is a stronger predictor of health than the presence of optimism (Scheier et al., 2021). Based on these findings, the present study examined the role of subjective well-being in the health effects of optimism and pessimism in romantic couples. It was expected that pessimism would be more strongly associated with both well-being and health than optimism, intra- and inter-personally. In addition, subjective well-being was hypothesized to mediate the health effects of optimism and pessimism. The study included two waves of data obtained from 153 opposite-sex couples. Self-report indicators of optimism, pessimism, subjective well-being, and health were assessed across waves. Cross-sectional and longitudinal actor-partner interdependence models showed that only the absence of pessimism, but not the presence of optimism, was associated with high levels and improvements in health (e.g., subjective health, sleep-efficiency, cold symptoms, chronic disease). In addition, pessimism was a stronger predictor than optimism of levels in some indicators of subjective well-being (e.g., negative affect, depressive symptoms). These effects were obtained intra- and inter-personally. Finally, levels of subjective well-being statistically mediated the effects of pessimism on levels and changes in health. The study’s results suggest that subjective well-being could represent a pathway that explains differential associations between pessimism and optimism with health, both intra- and inter-personally.


identifier: Herriot, Heather  (2021) Chronic Stress and HPA Axis Dysregulation in Older Adulthood: Protective Effects of Self-Compassion.  PhD thesis, Concordia University.

abstract: The aging population is the fastest growing segment of the population. With aging, there is an increase in the number of uncontrollable stressors that arise. Stress is known to have an impact on biological processes (e.g., HPA axis function) and downstream physical health outcomes (e.g., chronic illness). However, the exact pathophysiological patterns of HPA axis dysfunction that arise from chronic stress experiences is vastly understudied. In addition, little is known about psychological factors that promote adaption to stress and reduce the negative consequences of stress on health in old age. This dissertation sought to investigate the impact of stress experiences on older adult’s physical health and the benefits of the psychological trait self-compassion. Study 1 examined how chronic stress levels and changes predicted trajectories of diurnal cortisol (AUC and slope) over 12 years. Results indicated that older adults with high levels of chronic stress were likely to have significantly steeper declines in cortisol levels over the study. In addition, older adults with high and increasing stress levels displayed increasingly flatter cortisol slopes. Study 2 investigated cross-sectional associations between age-related stressors and diurnal cortisol, and whether self-compassion could buffer the impact of stress on cortisol patterns. The results found no association between age-related stress and diurnal cortisol. However, self-compassion moderated the association between age-related stress and cortisol. Specifically, older adults with higher levels of age-related stressors who were more self-compassionate were protected from higher levels of stress-related diurnal cortisol. Study 3 sought to explore the longitudinal health benefits of self-compassion across four years, and whether they vary for older adults in early vs. advanced old age. The results revealed that self-compassion predicted lower levels of daily physical symptoms on average for those in advanced old age (but not early old age). Self-compassion also predicted fewer increases in chronic illness over four years among those in advanced, but not early old age. Overall, this dissertation provides significant contributions to theory and research on stress, aging and health.


identifier: Chen, Xiaowei  (2021) Untangling Java Code Changes.  Masters thesis, Concordia University.

title: Untangling Java Code Changes

abstract: Pull requests are a critical approach for developers to collaborate in software development, which also initiates the following code review and integration. However, tangled pull requests can be introduced into version control systems via committing unrelated or multi-purposes code changes in one single pull request, which have been found to bring a negative impact on code recommendation systems and bug prediction models in the previous research. In this thesis, we conduct a case study on 640 pull requests among 8 popular open-source Java projects from GitHub. Through manual analysis, we find that 47% of the pull requests are tangled. In order to further understand the characteristics of tangled pull requests, we perform a qualitative annotation and classify the reasons for tangled pull requests. We find that 75% are tangled because bug fixing, feature improvement, or new feature adding are committed with an update in test code. The remaining 25% of pull requests are tangled because developers commit two or more unrelated bug fixing, feature improvement, test code adding or modifying, new feature adding, feature improvement and bug fixing, and other combinations inside one pull request. We also propose an approach to predict whether a pull request is tangled or not with an AUC of 0.87. Furthermore, we also predict whether two lines of code changes belong to the same task, which achieves an AUC of 0.74.


identifier: Fernandez Cruz, Javier  (2021) Using Intrinsic Dimensionality to Improve Dropout Regularization.  Masters thesis, Concordia University.

abstract: The intrinsic dimensionality (ID) of multi-dimensional data collections is one of their most fundamental characteristics. Estimates of ID provide an important notion of the complexity of the data, which, in turn, is crucial to selecting the right approach and designing effective machine learning models.  There is a wide range of applications for ID estimation, from widely used dimensionality reduction to adversarial attacks, outlier detection and search indices to more theoretical fields like similarity search, discriminability, graph construction, and extreme value theory.  However, the notions provided by ID estimations of the data stop at the threshold when designing machine or deep learning models, providing little to no insight when selecting model hyper-parameter configurations. In this work, we explored the idea of using a relation between the intrinsic and extrinsic dimensionality of an image manifold to provide an intuition for selecting an appropriate dropout rate to regularize neural networks in the context of image classification problems. We studied the characteristics of several ID estimators and applied them to image datasets and introduced a new formula to compute values for the dropout rate dependent on ID estimations. We empirically studied the effects of using this new rate by analyzing its effects in the training of several state-of-the-art image classification models on benchmark datasets. We showed that using this technique can consistently improve the performance of several well-established models.


identifier: tandon, swati  (2021) Analysis and Design of Series LC Resonant-Pulse Assisted Soft-Switching Current-Fed DC/DC Converters.  PhD thesis, Concordia University.

abstract:
The accelerating pace of electrification via renewable energy sources is shifting focus towards de-carbonization and distributed generation with the potential to combat increasing environmental crisis and to promote sustainable development. Renewable technologies have the potential to fulfil the electricity demand locally which eliminates the unwanted conversion stages, promoting DC microgrid concept, ultimately lowering the energy costs and easy energy access.
        Alternative energy sources such as solar photovoltaic (PV) and fuel cell along with energy storage systems are promising for DC microgrid applications. However, the effective integration of these alternative energy sources still remains a challenge due to their low voltage output, unregulated and intermittent characteristics issuing a requirement of a dedicated power conditioning unit. To revolutionize the way these alternative sources are interfaced with a high voltage DC microgrid or to the conventional ac grid, dc/dc converters are expected to be power-dense, compact and extremely efficient. Current-fed dc/dc converters have strong application potential owing to their inherent merits.
       Accomplishing the abovementioned objectives together with distinct merits offered by current-fed circuits, this thesis aims to exploit the quasi-resonance concept for achieving soft-switching and smooth commutation of the semiconductor switching devices. The proposed quasi resonant approach that utilizes the leakage inductance of transformer and a high frequency series resonant capacitor for a short period also termed as ‘resonant-pulse’, has been investigated in various current-fed converter topologies. Proposed converter class emphasize on simple and efficient design, without the use of additional snubber circuits and eliminates device turn-off voltage spike, which is a historical problem with traditional current-fed converters.
       In this thesis, at first the proposed series resonant-pulse concept is implemented in single-phase current-fed push-pull and half-bridge configuration. The converter operation, control and performance are investigated for low voltage high current specifications. These converter configurations demonstrate good efficiency and compact structure with only two switching devices and simpler gate control requirement because devices having common ground with power supply.
The idea has then been extended to modular current-fed full-bridge topology. The proposed series resonant-pulse assisted converter enables wide range ZCS and turn-off spike elimination across the semiconductor switches. Modularity of this converter allows easy scalability for high power and voltage levels with significantly lower current and voltage stress, making it suitable for relatively higher power industrial applications.
        Lastly, to achieve high power capability with high density, three-phase current sharing current-fed topology utilizing series resonant-pulse feature has been studied and investigated in detail. The proposed three-phase topology combines the benefits of current-sharing primary and load adaptive series resonant-pulse. As a result, these converters demonstrate promising attributes such as wide ZCS operation, reduced filtering requirement, lower component count, lower conduction losses etc.


identifier: Rad, Mahdi  (2021) Effect of Inventors’ Characteristics on Commercialization Potential of their Inventions: The Case of Nanotechnology in Canada.  Masters thesis, Concordia University.

abstract: Innovation may significantly contribute to building and maintaining competitive advantage of companies. It is therefore imperative to invest in research activities which will lead to innova-tive accomplishments that can be successfully patented. However, only a small portion of these patents will ever be commercialized in the form of a new product introduction or a patent license. The main purpose of this thesis is to examine various factors which might increase the commercialization potential of the patented inventions. We investigate the impact of collabo-ration patterns of inventors and also their various individual characteristics and the attributes related to their work on the commercialization potential of the inventions. While focusing on Canadian nanotechnology innovation ecosystem we exploit the data spanning 25 years of United States Patent Trademark Office (USPTO) patent documents. Based on the co-inventor-ship information captured in the patents the network of inventors’ collaborations is developed. To evaluate collaboration patterns of inventors the relevant structural properties assessing collaborative intensity and access to knowledge and ideas through the network are measured. Fur-thermore, various attributes and features of inventors related to their education, working expe-rience and to the characteristics of their workplace are collected via Google and LinkedIn. The statistical model assessing the impact of the various collaboration and individual characteristics of inventors on the commercialization potential of their inventions is then developed. The results show that those inventors who collaborate with higher number of other inventors and those who occupy more central positions in the collaboration network and thus enjoy an enhanced access to knowledge and ideas tend to produce inventions with higher commercialization potential. Moreover, the results also indicate that having graduate education in engineering and being employed in non-academic institution, especially in companies with lower number of employees are factors which may enhance the commercialization potential of the patented inventions as well.


identifier: Mirzaei, Morteza  (2021) Accurate and Precise Displacement Estimation for Ultrasound Elastography.  PhD thesis, Concordia University.

abstract:
Accurate and Precise Displacement Estimation for Ultrasound
Elastography
Morteza Mirzaei, Ph.D.
Concordia University, 2021

Elastography is a technique for detecting pathological tissue alterations by extracting
mechanical properties of the tissue. It can be performed using different imaging
modalities, including magnetic resonance imaging and ultrasound. Unlike biopsy that
is invasive and considers a small portion of tissue, elastography is a non-invasive
technique that interrogates a larger part of the tissue and reduces the probability of
missing abnormalities. UltraSound Elastography (USE) is an approach for detecting
mechanical properties of tissue by using ultrasound imaging. Ultrasound as an imaging
tool has emerged in the latter half of the 20th century and has become one of the
most popular imaging modalities. The main advantages of ultrasound imaging lie in
its noninvasive nature, low cost, convenience, and wide availability. USE may help in
early diagnosis which substantially increases the success probability of treatment. In
recent years, USE has been explored for several clinical applications including ablation
guidance and monitoring, differentiating benign thyroid nodules from malignant
ones and breast lesion characterization. Surgical treatment of liver cancer, assessment
of non-alcoholic fatty liver disease, assessment of fibrosis in chronic liver diseases, detecting
prostate cancer, differentiating abnormal lymph nodes in benign conditions
and brain tumor surgery are other relevant clinical applications of USE.
An important challenging step for USE is Time Delay Estimation (TDE) between
pre- and post-deformed tissue. TDE is an ill-posed problem since the 2D displacement
of one sample cannot be uniquely calculated based on its intensity. Moreover,
presence of noise due to speckles, out-of-plane movement, blood flow and other biological
motions affect the accuracy of TDE. The other limiting factors for TDE are
low resolution of ultrasound data, low sampling rate and lack of carrier signal in the
lateral direction. In this thesis, we propose high level techniques for increasing the
accuracy and preciseness of the estimated displacement.


identifier: Aminfar, Pouria  (2021) DYNAMIC DAMPING IN OPTICAL RECEIVERS.  Masters thesis, Concordia University.

title: DYNAMIC DAMPING IN OPTICAL RECEIVERS

abstract:
Today's telecommunications involves ever-increasing amounts of optical communication. Besides being an important component of the long-haul network, optical communications are also being used in data centers, circuit boards, integrated circuits, and the next generation of mobile networks. This thesis proposes an optical receiver in which the damping factor of both the transimpedance and post amplifiers is modulated synchronously with incoming data. Modulation of the damping factor allows the fast response of the low-damping factor while mitigating the intersymbol interference (ISI) associated with underdamped systems.
To investigate the modulated damping shunt-feedback transimpedance amplifier (SF-TIA), some methods, including switching the feedback resistor and modulating the damping factor by a sine wave, are used. Due to damping factor value limitation by changing the shunt-feedback and complexity of producing appropriate value of the sine wave with proper DC offset, amplitude and phase, damping factor modulation by a rail-to-rail square wave signal is presented where only phase adjustment is necessary and has better noise performance, Vertical Eye Opening (VEO) gain and gain to power ratio.
The extension of dynamic damping to the post amplifier is investigated through simulation at 10 Gb/s. A shunt-feedback TIA with cross-coupled inverters at the output, optimized to reach minimum input-referred noise is used as a reference for creating SF-TIA and Cherry-Hooper post-amplifier (CH-PA) blocks. By modulating the damping factor in both blocks, the proposed system achieves more than three times the VEO and lower input-referred noise compared to the optimized reference. Alternatively, an equal-gain modulated system has 40 % lower power consumption compared to the reference design.


identifier: Johnson, Carol  (2021) Language learners’ perceptions of automatic speech recognition as a writing tool: A Technology Acceptance Model analysis.  Masters thesis, Concordia University.

abstract:
Automatic speech recognition (ASR) has the potential to mitigate the cognitive burden of L2 writing by facilitating the text input process (using a skill most humans possess: speaking) and offering assistance in terms of linguistic form, thus allowing writers to focus on other aspects of the task (e.g., cohesion, content). ASR is accessible, easy to use, and free; more importantly, it fulfills Chapelle’s (2001) criteria of an effective CALL tool (e.g., it promotes authenticity, has potential for language learning). Despite these affordances, there is a dearth of studies examining the affordances of ASR for writing, and none examining the use of ASR with adult ESL writers.
This mixed-methods one-shot study examines L2 writers’ perceptions of using ASR to write using the Technology Acceptance Model (TAM; Venkatesh & Davis, 2000), based on three criteria: usefulness, ease of use, and intention to use. The participants were ESL students at an English-medium university (N=17). They were provided with training on Google Voice Typing in Google Docs and, as part of the treatment, carried out two ASR-based writing tasks over a two-hour period. To measure their perceptions of the target criteria, participants filled in a TAM-informed survey after completing the treatment. To further explore the participants’ perceptions of using ASR to compose their texts, semi-structured interviews followed the writing tasks.
Findings indicate positive perceptions of ASR in terms of usefulness (language learning potential) and its ease of use (e.g., user-friendly voice commands). As observed in the literature (e.g., Hsu., 2016; Tsai, 2015), these positive perceptions will lead to an intention to continue to use ASR, suggesting that the technology has L2 pedagogical potential.


identifier: Silva Trujillo, Daniela  (2021) Snacks: Portraits of a Global Pandemic.  Masters thesis, Concordia University.

title: Snacks: Portraits of a Global Pandemic

format: text video

abstract: Sharing food has always been a way to connect with other individuals, to represent oneself to others, to express your community to other communities, and in most cases, to pass down knowledge from generation to generation. You only need to have Wi-Fi on your phone to be connected to your home country with technology. This research-creation project addresses the interconnected areas of food studies, networked publics on Instagram and living through the first year of the COVID-19 pandemic. Through Smallest Narrative Units (Heinz Emingholz) the non-linear animated series entitled Snacks explores how individual Instagram users, that work within the food industry, discuss their love of food and their lived experience of a global pandemic. Both topics: food and the pandemic provide simultaneous paths to discussions of identity, representation, migration, community, care and security. Using research-creation, Loveless’s concept polydisciplinamory, online surveys, interviews and animation, I was able to address intersecting themes mentioned regarding food during a time of global crisis. The central claim of this work is that food stirs up personal and communal reflections, fosters a sense of community and provides a unifying common ground. This project resulted in an Instagram series of twelve animated episodes surrounding topics about food. Snacks: Portraits of a Global Pandemic makes a significant contribution by enriching the discussion of portraying food in a global pandemic, both in the series and in its development. This project also contributes to platform studies and animation studies by creating a non-linear non-fiction series for Instagram.


identifier: Huzaifa, Abdul Malik ORCID: https://orcid.org/0000-0002-0269-7089 <https://orcid.org/0000-0002-0269-7089>  (2021) System-Level Ventilation Considerations for Thermal Risk Assessment of Aircraft Systems in Conceptual Design.  Masters thesis, Concordia University.

abstract: The aviation industry is moving towards an environment-friendly future. Therefore, aircraft manufacturers are investigating new technologies to make future aircraft more efficient while striving at the same time to reduce development time and cost. These new technologies, such as more electric or hybrid-electric aircraft, require novel design tools to improve different aspects of aircraft design. One important aspect is the thermal analysis for aircraft systems, usually implemented during later stages as they require detailed information. The late consideration of thermal aspects can lead to delays due to redesign. With the recently developed Thermal Risk Assessment (TRA) approach, thermal architectures for systems can be defined in conceptual design. This thesis contributes to developing these conceptual thermal design tools by improving the TRA. The focus of this thesis is on system-level ventilation aspects; a so-called mainstream flow analysis is introduced. This analysis investigates the relationship between the location of the aircraft systems within equipment bays and the characteristics of the ventilation sources. New dimensionless numbers (DN) are defined to capture the effects of the mainstream flow. The development of the DN, their integration, and validation into the TRA is performed through several case studies using computational fluid dynamics (CFD). As a result, this new system-level ventilation analysis is introduced successfully into the TRA. The improved TRA shows satisfactory results for real-world aircraft equipment bays. As the analysis is based on DN, which is much faster than conventional CFD analysis and requires fewer inputs, suitable cooling strategies can now be developed during the conceptual design phase. In this way, thermal analyses can be integrated into a multidisciplinary design analysis and optimization framework, helping aircraft manufacturers develop more mature concepts with fewer iterations, particularly important for future unconventional, more electric, hybrid-electric, or all-electric aircraft configurations.


identifier: Xu, Wenting  (2020) A Quantitative-sectoral Approach to Business Risk.  PhD thesis, Concordia University.

abstract:
In the evolution of bank regulation over the last thirty years, the Value-at-Risk (VaR) measure has been a key metric in determining the amount of regulatory capital a bank must hold to deal prudently with its exposure to market, credit and operational risk. The security supposedly provided by VaR was certainly challenged by the financial crisis in 2008. The risk analysis in place at the time appeared to be too narrowly focused, as other issues (particularly liquidity risk) came to the fore.

This thesis has maintained the VaR objective, but extends the traditional analysis along two dimensions. First, we have analyzed a notion of business risk associated with fluctuations in a bank’s business income that are not tied to specific market, credit or operational events. Rather the fluctuations that we analyze are more the consequences of ongoing strategic decisions. Second, we have attempted to operationalize a sectoral approach where the losses potentially faced by a particular bank are those that are shared by its competitors.

We first develop in Chapter 2 a general framework for analyzing the core notion Residual Profit & Loss (RPL) using the income statements as reported in Capital IQ which also provides data on Interest Earning Assets (IEA). We then construct a business income data set based on RPL/IEA for a US Retail Banking Sector. There are twenty-two banks in the sector. RPL/IEA is determined for these banks over the period 2002-2015. Using more recent data, we will be able in the thesis to focus on the post-crisis 2008 period.

A data set is also constructed in Chapter 2 for the Canadian banking sector. It is more concentrated than the US sector studied and was less severely affected by the 2008 crisis. But the methodological approach followed in this chapter faces an additional complexity in so far as accounting standards were significantly changed in 2011. Moreover, it is not possible to reconstruct income statements prior to 2011 using the new standards. We pursue several avenues of adjustment to render the treatment of the data over the entire sample as coherent as possible. We then construct RPL/IEA for this typical banking sector following the same methodology as used for the US retail sector.

The remainder of Chapter 2 transforms the time series of business returns (RPL/IEA ratio) for each bank into the US and Canadian sectoral loss datasets. A loss (gain) for a particular bank is characterized as the deviation from its expected return defined as its average return over the sample.

Chapter 3 proposes two approaches to determine the values of VaR corresponding to two ways of looking at the loss datasets. One approach assumes that an individual bank’s loss time series follows a sectoral moving average process. The common parameter is estimated across the time series using maximum likelihood. The VaR for an individual bank can readily be retrieved in this multivariate characterization. The second approach ignores the time series dimension and pools the data into a single sample for each sector. In this context, we propose to use the saddlepoint approximation technique that involves the use of sample moments to estimate the percentiles of the underlying loss distribution.
The saddlepoint approach is not commonly use in the applied financial literature. The basic features of this technique are reviewed in Chapter 3 along with several examples to illustrate how it has been applied in finance. The second part of the Chapter presents an extensive Monte Carlo simulation study that contrasts the performance of the saddlepoint percentile estimates with those obtained by the maximum likelihood structural approach.

Chapter 4 returns to the calculation of business risk faced by the US and Canadian sectors considered in the thesis. For each of the associated business loss data sets, there are the two estimation procedures that were introduced in the previous chapter. The VaRs for different confidence levels are determined and contrasted across the two models for each of the two sectors. We include several comparisons with the economic capital held by specific banks in the Canadian sector.


identifier: Ansarian, Amin  (2021) Realistic Occlusion Augmentation for Human Pose Estimation.  Masters thesis, Concordia University.

abstract:
Occlusion occurs naturally in a high percentage
of real-world images. Handling occlusion has been a difficult challenge in human pose estimation methods, specially those using CNN. A main reason is the a lack of a proper dataset with an actual focus on realistic occlusion, prompting researchers to create datasets with synthetic (bounding-box based) occlusion, as a means of data augmentation. In this thesis, we investigate how to increase learning through data preparation (i.e., data-centric approach). To this end, we introduce a new realistic data augmentation approach built on top of an original (base) dataset (e.g., Human3.6m and MPI-INF-3DHP) that tackles this issue, creating realistic samples similar to those found in the wild. Arguing that CNN models pay higher attention to local as opposed
to global features, we define occlusion levels, process a large set of occluder objects from different categories, augment them adaptive to the joints types and to the size of the human subject, and effectively blend those occluders within the original RGB image from the base dataset. We, then, test top-performing CNN-based 2D and 3D human pose estimation models with and without our occlusion-augmented datasets (\textit{RealPose}). Our experiments show that a significant  drop in accuracy of these CNN models under occlusion. When we then train them on RealPose, we observe a major increase in accuracy under occlusion, without any change to the models themselves. Achieved results indicate the effectiveness of the proposed data augmentation method in tackling the occlusion issue both in the 2D and 3D models, with a significantly much more accuracy increase of the 3D models. We have trained and tested the models under different dataset combinations such as "training on the original dataset but testing under the augmented dataset" or "training and testing with the mixed original and augmented dataset". A significant outcome is that, our data-centric approach results in a higher accuracy of CNN models trained under occluded samples but tested under the original (not-occluded) samples, indicating the model achieves a higher understanding of the dependency of different joints induced to it. Proposed approach is dataset and network independent, i.e., researchers can apply our approach (using its open-source code) to any dataset and feed the result to any human pose estimator.


identifier: MacDonald, Sydney  (2021) Predicting Functional Outcomes of Open Latarjet Surgery Patients.  Masters thesis, Concordia University.

abstract:
This thesis aims to explore the predictive ability of pre-operative patient characteristics on functional outcomes following an open Latarjet procedure for shoulder instability. A prospective cohort analysis of patients who had received an open Latarjet procedure from September 2009 to February 2021 was conducted. Potential predictors included general patient information (age, number of dislocations, sport level before surgery, joint hypermobility), pre-operative scores on QuickDASH and WOSI questionnaires, and pre-operative measurements of shoulder ROM, strength, and proprioception. Data was collected during a pre-operative evaluation, and follow-up measures were gathered at 6- and 12-months after surgery. Data analysis included one-way ANOVAs to determine if outcomes improved over the follow-up periods; univariate and multivariate analyses identified predictive variables of function and quality of life measures.
For general patient information and pre-operative functional scores, results identified joint hypermobility, sport level, and pre-operative WOSI scores as predictors of post-operative function and quality of life. Regarding shoulder ROM, strength, and proprioception, there appears to be a relationship in their predictive ability of post-operative functional outcomes. However, a larger sample size is needed to substantiate these results.
These results could carry important clinical implications, as the significant predictors of surgical outcomes have the potential to be modified or improved upon prior to surgery. Using these predictors, surgeons would be able to make predictions regarding the individual needs of their patient. By incorporating preoperative functional measures that can be altered, patients may be able to reduce their levels of preoperative dysfunction yielding a better outcome from their surgery.


identifier: Rezaiefar, Ali ORCID: https://orcid.org/0000-0001-8018-6498 <https://orcid.org/0000-0001-8018-6498>  (2021) Large Displacement Analysis and Design of Stiffened Plates with Parallel Ribs in Large Industrial Ducts.  PhD thesis, Concordia University.

abstract:
The structural design of stiffened plates of the walls of rectangular-sectioned industrial ducts and similar structures is conventionally based on the linear beam theory assuming that the displacements are small and the membrane forces that generate in the panel plate are negligible. The design of such stiffened plates is divided into two main steps where the panel plate and the rib stiffener are designed sequentially. Depending on the nature of the loads applied to the industrial duct, a third step might involve determining the vibration frequency of the panel plates for resonance verifications.
In the first phase of this thesis, the conventional design method for the panel plate is studied in order to examine the effects of large displacements on the behaviour of the structure and ultimately present a new design approach accordingly. Two different sets of formulas are presented based on Finite Element analysis of rectangular plates with relatively long aspect ratios that estimate the maximum stress and deformation in the typical and edge panels of stiffened plates. These formulae are then applied to establish empirical design equations for the panel plates. The new design approach is capable of reducing the panel plate thickness significantly in comparison with the conventional method.
In the second phase of the thesis, the structural design of the rib stiffeners is evaluated through a comparison between the conventional design which is based on Modelling the stiffened plate using an Equivalent Beam Analogy (EBA) and calculating the geometrical cross-sectional properties of it in linear beam theory, and FE analysis of the stiffened plate using shell elements with and without the consideration of large displacement effects. It is shown that the EBA and linear beam theory, as well as the FE using small displacements, are not relevant for the analysis and design of stiffened plates. In this phase, it is shown that the load-displacement behaviour of stiffened plates with parallel ribs could be different under positive and negative pressures as the membrane forces generated in the panel plate would affect the overall behaviour of the stiffened plate differently.
The third phase of the thesis provides means for obtaining the first three significant vibration modes for rectangular plates based on mass participation ratios. A non-dimensional frequency parameter is presented which results in the vibration frequency of rectangular plates at each of these three significant modes. Various aspect ratios and four combinations of boundary conditions at the plate edges are studied, and a correlation between the nonlinear load-deformation behaviour of the panel plate and its vibrational behaviour is also presented accordingly. It is demonstrated that the vibration frequency of the studied rectangular plates increases significantly upon increasing the applied lateral pressure if the large deformation effects are considered in the analysis. The easy-to-follow method of frequency calculation presented in this paper is useful for assessing the dynamic characteristics of rectangular plates with or without lateral pressure that are subject to vibration.


identifier: Zunair, Hasib  (2021) Designing Efficient Deep Learning Models for Computer-Aided Medical Diagnosis.  Masters thesis, Concordia University.

abstract:
Traditional clinician diagnosis, which requires intensive manual effort from experienced medical doctors and radiologists, is notoriously time-consuming, costly and at times error prone. To alleviate these issues, computer-aided diagnosis systems are often used to improve accuracy in early detection, diagnosis, treatment plan and an outcome prediction. While these systems are making strides, significant challenges remain due the scarcity of publicly available data, high annotation cost, and suboptimal performance in detecting rare targets. In this thesis, we design efficient deep learning models for computer-aided medical diagnosis. The contributions are two-fold: First, we introduce an over-sampling method for learning the inter-class mapping between under-represented class samples and over-represented samples in a bid to generate under-represented class samples using unpaired image-to-image translation. These synthetic images are then used as additional training data in the task of detecting abnormalities (i.e. melanoma, COVID-19). Our method achieves improved performance on a standard skin lesion classification benchmark. We show through feature visualization that our approach leads to context based lesion assessment that can reach an expert dermatologist level. Additional experiments also demonstrate the effectiveness of our model in COVID-19 detection from chest radiography images. The synthetic images not only improve performance of various deep learning architectures when used as additional training data under heavy imbalance conditions, but also detect the target class with high confidence.

Second, we present a simple, yet effective end-to-end depthwise encoder-decoder fully convolutional network architecture, dubbed Sharp U-Net, for binary and multi-class biomedical image segmentation. Instead of applying a plain skip connection such as U-Net, a depthwise convolution of the encoder feature map with a sharpening kernel filter is employed prior to merging the encoder and decoder features, thereby producing a sharpened intermediate feature map of the same size as the encoder map. Using this sharpening filter layer, we are able to not only fuse semantically less dissimilar features, but also smooth out artifacts throughout the network layers during the early stages of training. Our extensive experiments on six datasets show that the proposed Sharp U-Net model consistently outperforms or matches the recent state-of-the-art baselines in both binary and multi-class segmentation tasks, while adding no extra learnable parameters.


identifier: Heidarzadeh, Hamidreza  (2021) The effect of methodological flexibility on membrane protein classification.  Masters thesis, Concordia University.

abstract:
Reproducibility, the ability to reproduce computational results using identical data and software, is a cornerstone of the scientific methodology. However, through the past decade, several studies revealed a widespread lack of results’ reproducibility, to the point that the existence of a reproducibility crisis is now acknowledged in various fields. In Machine Learning, given the flexibility available in various phases of constructing a computational model, the experiments are not immune to reproducibility issues either. In case of imbalance learning for problems with multiple classes, the problem is even more severe since there are more parameters in play for constructing a model. The resulting reproducibility challenges have implications in various disciplines including bioinformatics, the primary focus of our study.

Researchers have already taken counter-measures proposing various recommendations for having results’ reproducibility in this domain of study. Some conferences have even adopted new measures in that regard. Following those guidelines could ensure reproducibility to an agreeable degree in balanced problems. In this work we demonstrate that in an imbalanced scenario, even in its basic form, a study report with a fair amount of details, could reproduce a wide range of results if methodological flexibility is permitted.


identifier: Ashouri, Negin  (2021) Ensemble Graph Neural Networks on Melanoma and Cervical Cancer Screening Datasets using SLIC Superpixels.  Masters thesis, Concordia University.

abstract:
Graph neural networks (GNNs) have become the standard procedure to deal with graphstructured data and data in non-Euclidean spaces. Since 2017, numerous researchers have been
using GNN models in their experiments. However, despite GNNs’ recent rapid growth, there are not yet many real-world applications that benefit from these models. In this thesis, we use GNNs
as image classifiers. To improve the efficiency and reduce the complexity of the models, we first generate graphs from the images by creating superpixels of the images and use them as our graph nodes instead of individual pixels. Then, we define edges on these nodes based on the distance
of each superpixel to their closest ones. We propose two ensemble frameworks containing a pre-trained ResNet18 and two Graph Neural Network (GNN) models (GAT and GIN). We call these
frameworks GATRes and GATGIN, respectively.
We test these frameworks on two real-world medical applications: Cervical Cancer Screening and Melanoma detection. Cervical cancer is among the top four common cancer in women worldwide.
Cervical cancer can be easily prevented if caught in its pre-cancerous stage. Determining the appropriate treatment method depends on patients’ physiological differences. A treatment that
works effectively for one woman may obscure future cancerous growth in another woman due to differences in the type of their cervix. In this thesis, we experiment with multiple GNNs on this
dataset to distinguish the cervix types and examine if these models enhance detection performance and accuracy.
The other problem we consider is Melanoma skin cancer. Melanoma is the most lethal skin cancer. If melanoma gets diagnosed in the early stages, the patients’ survival rate will increase significantly. This research applies GNN models on the Melanoma dataset to discriminate between melanoma and benign skin lesions.
We show that our models’ sensitivity and accuracy outperform the individual models in our classification tasks. Our GATRes model also outperforms the accuracies achieved by previously
published papers on the Cervical Cancer Screening dataset.


identifier: Noel, Duane D.  (2021) Assessing the influence of the Pacific Decadal Oscillation and the Atlantic Multidecadal Oscillation on discharge variability in western North America.  Masters thesis, Concordia University.

abstract: The frequency of natural hazards in North America presents a significant challenge for governments due to the damages they cause to the environment. Floods are severe hydrological events caused by spring snowmelt and intense rain events. Flood frequency analysis studies assumes that annual peak flood events occur independently of each other, regardless of previous flood events (the independent and identically distributed (i.i.d.) assumption); however, annual peak flood records do not necessarily appear to conform to these assumptions. First, a review of the literature on the effects of climate oscillations on extreme flood frequencies in North America was conducted. Then, the i.i.d. flood event assumption was tested by analyzing the effects of the Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO) on 250 naturally flowing annual peak flood records across the entire western North American margin. Using permutation tests on quantile-quantile (Q-Q) plots, I found that the PDO has a greater impact on the magnitude of annual peak floods than the AMO. Twenty-six percent of the gauges have higher magnitude annual floods depending on the PDO phase (p < 0.1). Next, I examined the interacting effects of the PDO and AMO on the frequencies of lower and upper quartile annual peak floods, and found reinforcing, cancelling, and dominating effects. Since these two climate oscillations have significant effects on the magnitudes of annual peak floods, the i.i.d. assumption does not hold. Hence, I advocate for the need to re-assess baseline flood analysis in western North America to improve flood management strategies.