identifier: Shoukry, Moataz  (2020) Unmanned Aerial Vehicles for 5G and Beyond: Optimization and Deep Learning.  PhD thesis, Concordia University.

abstract: Aerial platforms and, more precisely, Unmanned Aerial Vehicles (UAVs) or drones augmented with ubiquitous computing, processing, and wireless communication technologies are expected to play an important role in next-generation cellular networks. The flexibility and controllable mobility of UAVs render them suitable to be part of access. Nonetheless, combined terrestrial and UAV communication improving network coverage and Quality of Service by leveraging line-of-sight communication as well as minimizing the delay and age-of-information for UAV-to-ground communication. Despite its numerous advantages, the deployment of UAVs faces different challenges with respect to wireless networks, ranging from radio resource management to UAVs’ trajectory under energy limitation constraint and minimal knowledge of the environment. To this end, this dissertation aims to address the challenges in the efficient deployment of UAVs in future networks under various performance metrics. The key goal of this dissertation is to provide the analytical foundations for deployment, learning, in-depth analysis, and optimization of UAV-assisted wireless communication networks. Towards achieving this goal, this dissertation makes significant contributions to several areas of UAV-assisted wireless communication networks within the contexts of static environments as well as high mobility environments. For the deployment of UAVs in static environments such as Internet of Things (IoT) wireless networks, various tools such as optimization theory and machine learning frameworks are employed to enable UAV trajectory design under different scenarios and performance metrics. Results demonstrate the effectiveness of the proposed designs. In particular, UAVs adapt their mobility and altitude to enable reliable and energy-efficient communication, to maximize service for IoT applications, and to maintain the freshness of information. For the deployment of UAVs in high mobility environments such as vehicular networks, unique design challenges are considered and carefully handled to guarantee the effective performance of the UAV. Particularly, the high mobility of the vehicles leads to distinct network conditions and changes the network topology. The challenge here is that designing an efficient deployment of UAVs while considering the complex and dynamic network conditions is not a trivial task. This challenge was addressed through comprehensive studies that led to effective, robust, and high-performance solutions. Different performance metrics such as coverage, age of information, throughput, and Quality of Service were evaluated and compared with other approaches. Results shed light on the trade-offs in the vehicular network such as throughput-latency when exploiting UAV mobility for service. The findings in this dissertation highlight key guidelines for the effective design of UAV-assisted wireless communication networks. More insights on the efficient deployment of UAVs in static and high mobility environments are provided in order to assist and enhance communication in future networks while considering the unique features of UAVs such as their flight time, mobility, energy budget, and altitude.


identifier: Yang, Jie  (2021) Can You Resist Temptation? The Potential of One-Stop Online Purchasing.  Masters thesis, Concordia University.

type: Thesis NonPeerReviewed

abstract:
This thesis uses the engagement-generation process to examine how social presence and shopping convenience affect consumer participation in a social commerce (s-commerce) context. RED, a novel social commerce app, is used to determine whether different formats of content result in different levels of social presence and whether consumers’ purchase intentions varied when exposed to different content. This thesis also suggests methods for improving online purchase methods to increase customer engagement and online purchases. An experimental design was used, and the data was collected from a random sample.
Results suggest that video conveys a higher level of social presence than text, but format does not significantly affect online purchase intention. To increase user engagement on the social commerce platform, marketers can use more text to deliver content and improve the level of purchase convenience at the same time. This improves user purchase intention. This study centers on the interactive effects of social presence and online purchase convenience and opens a new line of research on different formats of content on social commerce platforms.
Key words social commerce; social presence; online shopping convenience; online purchase intention


identifier: Maraouch, Ghassan  (2021) Prosthetic mitral valve orientation and its impact on the flow dynamics in the left ventricle.  Masters thesis, Concordia University.

abstract: Severe mitral regurgitation is a complication that reduces the quality of life of those affected and left untreated, it can lead to heart failure and potential death. With the recent success of transcatheter aortic valve replacement surgery reducing the risk associated with open heart surgery, attention has been focused on performing a similar approach for mitral valve replacement. Transcatheter mitral valve replacement has proven to be more challenging; one of the associated complications is the potential misalignment of the mitral valve that alters the flow dynamics occurring in the left ventricle. An in-vitro experiment was performed to study the change in the flow dynamics associated with increasing misalignment severity. Three different valve orientations were investigated: a healthy case to use as a baseline, a slightly angled case such that the valve is aligned with the apical septal wall and a highly angled case that has the valve aligned in the basal septal wall. Each valve orientation was tested over a range of heart rates corresponding to 40, 60, 80, 100 and 120 beats per minute while maintaining a constant stroke volume. A Eulerian analysis was performed on fluid mechanics properties including the kinetic energy, viscous energy dissipation and circulation. The healthy case was determined to minimize viscous energy dissipation and maximize systolic kinetic energy. Circulation in the altered valve orientations had a reversed direction relative to the healthy case. A Lagrangian analysis was completed to quantify the amount of stasis, which was determined to be minimized in the healthy case.


identifier: Rafael Guaraldi da Silva, Pedro  (2021) A Sensitivity Analysis Method for the Update of the National Energy Building Code of Canada (NECB-2017).  Masters thesis, Concordia University.

abstract: An increasing trend in energy consumption can be seen worldwide. Projections for the world energy consumption indicate an increase of nearly 50% by 2050. In Canada, the electric power selling price has risen by 250% in the last four decades. The rising trend in energy consumption and cost is a pressing concern. Within that trend, residential, commercial, and institutional buildings are big contributors, accounting for 28% of the total secondary energy use in Canada. As a direct response to the increase of energy use in buildings, minimum energy efficiency requirements were proposed and compiled into energy standards, seeking to provide guidelines and instructions in the design, construction, and operation stages. These standards proved to be a powerful tool to improve energy efficiency, especially if adopted by state and federal legislators as mandatory requirements. Given the major role that such standards play, attention is drawn to the process used in updating these energy efficiency requirements. This research proposes a method for identifying the most impactful factors in the energy efficiency of buildings and for quantifying the impact that changes in these factors have on a range of energy related KPIs. This method can help policy makers and parties involved in the update of building energy code requirements by providing a metric to prioritize changes based on their impact. Additionally, the proposed method can aid in the allocation of R&D resources in the proposal of improvements to the building envelope and HVAC equipment, based on the impact of each of the studied improvements.


identifier: Bhise, Naitik, Krzyżak, Adam and Bui, Tien D.  (2021) Attention on Attention for Text to Image Synthesis using Mode-Seeking Loss Function.  Masters thesis, Concordia University.

creator:
Bhise, Naitik
Krzyżak, Adam
Bui, Tien D.

abstract: Text to Image Synthesis is a burgeoning field that has sprung up in the research community in the last few years. Generative Adversarial Networks form the basic component of modern research as many architectures are built around this particular type. This thesis is an attempt to develop a new technique and architecture to compete with the recent state-of-the-art models. The research around the text to image synthesis is conducted using two approaches by working with the modification of the loss and then the change in architecture. In the first approach, we sample two noise vectors to generate two different output images. The model is trained by a mode-seeking loss function which maximizes the ratio of the l2-norm of difference between the two images to the l2 norm of difference between noise vectors. The second approach deals with increasing the attention between the text and the image by introducing the Attention on Attention architecture in the AttnGAN network. We find that a combination of two approaches produces good quality images and better attended on their text descriptions.  The metric scores of Frechet Inception Distance and Inception Scores are used to evaluate the results. The datasets used in this research are Microsoft COCO and CUB Birds. A comparison study of the obtained results with the past state-of-the-art models is conducted and presented in this thesis.


identifier: Zaroubi, Liana  (2021) The Chemical Ecology of Geosmin.  Masters thesis, Concordia University.

title: The Chemical Ecology of Geosmin

format: archive text

abstract: Known as the smell of earth after rain, geosmin is an odorous terpene detectable by humans at picomolar concentrations. Geosmin production is heavily conserved in actinobacteria, myxobacteria, cyanobacteria, some fungi and red beets (Beta vulgaris L.), suggesting it strongly contributes to the fitness of these organisms. Prokaryotes produce geosmin through the terpene cyclase “geosmin synthase” converting germacradienol into geosmin via isoprenoid pathways (methylerythritol phosphate, mevalonate or leucine-dependent). However, the universality and ecological role of geosmin is poorly understood. I theorized that geosmin is an aposematic signal used to indicate the unpalatability of toxin-producing microbes, discouraging predation by eukaryotes. Consistent with this hypothesis I have found that geosmin reduces predation of Streptomyces coelicolor and Myxococcus xanthus by the bacteriophagous Caenorhabditis elegans. Predation was restored by the removal of both terpene biosynthetic pathways or deletion of the C. elegans ASE sensory neuron and resulted in the death of the nematodes. Geosmin itself was non-toxic. This is the first warning chemical to be identified in bacteria or fungi, and suggests molecular signalling affects microbial predator-prey interactions in a manner similar to the well-studied visual markers displayed by poisonous animal prey. In line with geosmin being a warning chemical, I also determined from a bioinformatics analysis that geosmin synthase was acquired from a distant past through horizontal gene transfer with Actinobacteria as the ancestral genetic reservoir. In addition, my work also suggests that several genes not directly involved in the biosynthesis of geosmin nevertheless support its activity. The investigation of these genes may enhance our understanding of the biosynthesis and regulation of geosmin and terpenes in prokaryotes.


identifier: Ghooshkhaaneie, Seyyed Vahid  (2021) Manipulability Optimization for Kinematically Redundant Rehabilitation Robots.  Masters thesis, Concordia University.

abstract: In this thesis, the dexterity of manipulators with rehabilitation applications is optimized in terms of manipulability. The optimal design is applied to non-redundant and redundant manipulators. For the non-redundant case, the manipulability improvement is realized by maximizing the link lengths of the manipulator. For the redundant case, the manipulability is maximized in terms of the optimal link lengths and optimal configurations using an exhaustive search. The design is fulfilled for healthy and faulty Jacobians. It is shown that the minimum degree of redundancy to apply fault-tolerant design is two. For the faulty case, the fault-tolerant relative manipulability is maximized, which shows how much dexterity is maintained in post fault conditions. The simulation results exhibit the effectiveness of the proposed configuration.


identifier: Mao, Yuhao  (2021) A Framework Design for Integrating Knowledge Graphs into Recommendation Systems.  Masters thesis, Concordia University.

abstract: Online recommendation is a significant research domain in artificial intelligence. A recommendation system recommends different items to users, and has applications in varied domains, including news, music, movies, etc. Initially, recommendation systems were based on demographic, content-based filtering and collaborative filtering. But collaborative filtering often suffers from sparsity and cold start problems, therefore, side information is often used to address these issues and improve recommendation performance. Currently, incorporating knowledge into the recommendation algorithm has attracted increasing attention, as it can help improve recommendation system performance. Knowledge graph representation and construction, and recommendation system development are independent but related; the triples of knowledge graph form the input to the recommendation system. While, there are a number of independent solutions for each of these two tasks, currently, there is no existing solution that can combine the construction of knowledge graph and input it to the recommendation system to provide an integrated work pipeline. Our major contribution is a modular, easy to use framework solution that fills this gap, essentially enabling integration of a structured knowledge graph and a recommendation system. Our framework provides multiple functionalities, including cross-language invocation and pipeline execution mechanism, and also knowledge graph query, modification and visualization. We instantiate our implementation of the proposed framework and evaluate its performance to show that we achieve higher accuracy in recommendations by using side information extracted from knowledge graphs. Our framework addresses the complete pipeline from constructing structured data knowledge graph to training recommendation model to incorporating the recommendation system into application domains.


identifier: Crowdis, Kelly K.  (2021) Let's Talk About It: Does Discussion Impact Teacher Knowledge in a Professional Development Workshop?  Masters thesis, Concordia University.

abstract: Over several decades professional development for teachers has evolved; in some cases, isolated workshops have made way for professional learning communities in an effort to better support teachers in their practice. This investigation explored whether discussion, a key element in professional learning communities, would impact teachers’ knowledge and satisfaction, in a 2-day isolated workshop. Fifty-three in-service teachers received 3 hours of professional development on the topic of promoting the love reading in their students. The experimental manipulation revolved around the opportunities for discussion during the workshop. The intervention group discussed the material in an environment that promoted collaboration. The control group was deterred from discussion. The dependant variables were teacher knowledge, teacher satisfaction with the workshop; and teacher interest in collaboration with colleagues, collaboration with a facilitator, and appreciation of types of professional development. The results from the mixed ANOVA showed that the 2-day intervention was effective in increasing teachers’ knowledge. However, there was no difference between the two discussion groups. In addition, the results of an independent t-test found a significant difference for the discussion group’s propensity to collaborate with colleagues. No other differences between the groups were observed. The most common response from both groups indicated high satisfaction for the workshop. It would appear that high-quality, isolated workshops still have their place for delivering pertinent, current content on the topic of teaching reading to children.


identifier: Greiss, Jessica  (2021) Elementary School Teachers’ Perspectives on Report Card Grading.  Masters thesis, Concordia University.

abstract:
Report card grading in the Quebec education system is an inevitable process that all teachers must endure. This study explored ten elementary teachers’ perspectives on their grading and report card systems through semi-structured interviews and a questionnaire. The two main research questions were: 1) How do elementary school teachers formulate their report card grades? and 2) What do teachers believe these grades are intended to communicate? Through analyzing the teachers’ responses, the inaccuracy of report card grades came to light, as it has for decades prior. It is evident that teachers are trying to use report card grades to represent the whole child’s experience in the classroom, while including a multitude of factors in their grades, also known as ‘hodgepodge grading’ (Brookhart, 1991). This type of grading makes it difficult for parents and students to understand what the grade symbolizes in relation to the children’s learning. Furthermore, teachers do not agree on what report card grades should be representing – thus creating more confusion for parents and a greater gap amongst teachers’ perspectives. This study complements the research that explores the reliability and validity of report card grades based on the 100 percent scale.

Keywords: reliability, validity, hodgepodge grading, academic achievement, report cards


identifier: Tan, Yingcong  (2021) Learning Linear Programs: Inverse Optimization as a Form of Machine Learning.  PhD thesis, Concordia University.

abstract:
Conventionally, in an optimization problem, we aim to determine the values of the decision variables to minimize the objective function subject to the constraints. We refer to this problem as the forward optimization problem (FOP). In an inverse optimization (IO) problem, the goal is to determine the coefficients of an FOP such that an observed solution becomes an optimal solution of the learned FOP model.
In this dissertation, we focus on the inverse linear optimization problem whose FOP has the form of linear programming.
We adopt an interdisciplinary approach,  leveraging concepts and methods from machine learning to address a very general form of this problem.

Firstly, we study the general form of the inverse linear optimization problem, that is, learning all model coefficients individually or jointly where the unknown model coefficients may or may not depend on exogenous parameters. We are the first to cast the IO problem as a form of deep learning and solve it with a gradient-based algorithm. To compute the gradients, we differentiate through the steps of an optimization process, in particular, the Barrier interior-point method. We develop new sets of benchmark instances and show good performance of our algorithm on different IO tasks: 1). learning a cost vector of linear program; 2). learning cost vector and constraints of a linear program jointly; 3). learning unknown parameters in the objective and constraints of a parametric linear program.
To the best of our knowledge, this algorithm is the first IO approach in the literature to be able to handle all three types of tasks.

Secondly, we formulate the inverse linear optimization problem as a bilevel optimization problem and explicitly encode constraints in the outer problem to ensure that observed solutions remain feasible with respect to the constraints. Again by leveraging a machine learning perspective on inverse linear optimization, we develop a general-purpose framework to solve the bilevel model with gradient-based algorithms. We investigate different methods for differentiating through an optimization problem and specialize them to LP. Additionally, we focus on an objective-based loss function and derive a closed-form expression for computing gradients.
Experimental results show that our framework is capable of solving synthetic parametric linear program and multi-commodity flow problem instances which could not be previously solved by methods in the IO literature. Additionally, we show that our closed-form expression is orders of magnitude faster than other methods for computing the gradients.

Finally, we focus on a special case of learning the objective only. We present four different methods for solving this problem, including three mathematical formulations and one general gradient-based algorithm. We test all four methods on synthetic parametric linear program and multi-commodity flow problem instances, and show that all four methods can successfully solve all experimental instances. All three mathematical models are solved in a commercial optimization solver and, due to their specialized nature, outperform the more generic gradient-based algorithm in runtime. Additionally, we show that the parametric linear programs learned from the KKT-based and strong duality-based formulations produce the best predictions on testing data.

In summary, the main contribution of this dissertation is the development of a general gradient-based framework which is able to solve problems that were previously not tackled in the IO literature. In addition, we extend and unify models for the special case of learning the objective only, which has been the focus of previous IO work. This dissertation unifies machine learning and inverse optimization both at the modelling and algorithmic levels.


identifier: Rodier, Simon  (2021) Uncovering Latent Topics in Text: Using Topic Models to Identify Discussion Themes in the Brett Kavanaugh Controversy.  Masters thesis, Concordia University.

abstract: Social media texts are abundant and generated at a rapid pace; often, they discuss contentious issues in ways that can be extreme, with people defending counter-intuitive points of view. This project develops an understanding of how individuals discuss contentious issues in online fora. It examines gender as a contentious issue, and also examines the controversy surrounding Brett Kavanaugh's nomination to the U.S. Supreme Court amidst sexual assault allegations in 2018 as a gendered controversy. Social media posts about the controversy were collected from reddit and analyzed with a framework using topic models, which help uncover latent topics in text. Significant discussion throughout the corpus centered on four major themes: the search for and evaluation of evidence; the importance of a Supreme Court nomination and of an investigation into the allegations; sexual assault and gendered perceptions and expectations; and finally, a discussion of the judiciary hearing into the allegations. Discussion of the results suggests that notions of power and loss aversion may be at play throughout the corpus. Additional discussion reflects on the use of topic models as a qualitative research tool, suggesting that they can be an effective way of exploring broad themes within larger corpora.


identifier: Deniz, Başar ORCID: https://orcid.org/0000-0002-0197-2747 <https://orcid.org/0000-0002-0197-2747>  (2021) A Dismissed Heritage: Contemporary Performance in Turkey Defined through Karagöz.  PhD thesis, Concordia University.

abstract: This study focuses on the aesthetics of the contemporary theatre of Turkey through the focal point of Ottoman non-religious and urban performance forms, and particularly the medium of shadow puppetry known as Karagöz. The major signature of Karagöz is its metatheatricality, which was incorporated into the contemporary theatre of Turkey through the various methods discussed in this thesis. Adaptation, epic theatre, ‘two and a half dimensions,’ and ‘narrative theatre’ are all methods that serve this culturally-rooted metatheatrical performance paradigm. As a through line, while tracing the aesthetic hybridities, Western influences, and organizational structures that shaped the contemporary theatre field of Turkey through multiple case studies, this thesis centers itself around the focus of illustrating the patterns of how the archetypes, elements, and techniques of Karagöz were recycled and re-invented on the contemporary stage. This overall metatheatricality sets up the dramaturgy and acting style through its open form, and through the direct engagement of the performers with their audiences.


identifier: Sitnikov, Dmitri  (2020) Development of Methods for Global and Targeted Metabolomics Analysis of Biological Fluids.  PhD thesis, CONCORDIA UNIVERSITY.

abstract:
Development of Methods for Global and Targeted Metabolomics Analysis of Biological Fluids Dmitri Sitnikov, Ph.D.
Concordia University, 2021
Protein precipitation with organic solvents is the most common extraction method used for global metabolomics of human plasma. This standard method has broad selectivity but does not provide good coverage of low abundance metabolites. Increasing the metabolite coverage by parallel analysis of plasma samples prepared using different organic solvents is inefficient due to the low orthogonality of their selectivity. Moreover, there is an increasing demand for more selective sample preparation methods suitable for targeted and untargeted metabolomics analysis of biofluids that can also provide better coverage of metabolites missed by current standard workflows. To achieve these goals, a novel sequence of orthogonal but complementary extraction methods was designed and evaluated after performing a quantitative systematic side-by-side comparison of seven extraction protocols with different selectivity to establish the most orthogonal combinations with good analytical performance. A novel sequential solid-phase extraction protocol was introduced to fractionate the metabolome into anion, cation, neutral, and zwitterion fractions, followed by a rigorous analytical assessment. The improvement in metabolome coverage in metabolomics study could be achieved also by analyses of alternative samples such as oral fluid. Therefore, the final goals were to evaluate oral fluid as a sample source for targeted metabolomics analysis via the development and validation of a liquid chromatography with tandem mass spectrometry assay and accumulate sufficient background knowledge to handle this sample type in future developments.
The execution of the first objective, i.e., the side-by-side comparison of solvent precipitation methods confirmed their low orthogonality and was accompanied by severe matrix effects in comparison to more selective methods. The comparison of solid-phase extraction (SPE) and liquid-liquid extraction methods revealed their orthogonal metabolite coverage to other methods. However, further experiments showed that methyl tert-butyl ether incompletely removed lipids, which resulted in the significant and undesirable splitting of lipids between aqueous and organic layers. Thus, the final SPE sequential fractionation protocol combined sample deproteinization by methanol followed by the sequential SPE executed on mixed-mode strong anion-exchange and mixed-mode strong cation-exchange polymeric sorbents. This produced four fractions enriched in metabolites with distinct ionic properties providing flexibility to analyze the fraction individually or in strategic combinations tailored to various mass spectrometry methods. The final protocol resulted in a 1.6-fold increase in total metabolite coverage compared to methanol precipitation with a 2-fold increase in the analysis time. The method demonstrated excellent signal repeatability for both targeted (relative standard deviation < 13%) and global (relative standard deviation < 30% for 75% metabolites) metabolomics. Moreover, excellent separation of anion and cation metabolites (< 4% overlap) and small (< 27%) overlap between other pairs of metabolite classes allow supplementary assignment of ionic properties to unknown metabolites that can aid metabolite identification. The utility of the above sequential solid-phase extraction method for fractionation of the polar metabolome can, in future, extend beyond plasma to other biofluid types, such as oral fluid. Oral fluid allows portable sample acquisition and reflects the composition blood at least for several metabolites. Moreover, the similar first step (methanol precipitation) between two methods promised easier and faster transfer of the solid-phase extraction protocol from plasma to oral fluid. Two model analytes cortisone and cortisol were selected for a preliminary study in oral fluid to serve as standard metabolites in the future implementation of solid-phase extraction protocol. Their selection was driven by their biological and clinical role and a commercial availability of stable isotope labelled standards. Methanol precipitation and a short reversed-phase chromatography run were combined with tandem mass spectrometry analysis. The successful development and validation of the method revealed an accurate, precise (< 15% variability), and sensitive (low limit of quantitation = 0.31 ng/mL) high-throughput assay, whose selectivity outcompeted an immunoaffinity method, while requiring only 30 µL of oral fluid sample.
In summary, this thesis establishes the first steps towards the adaptation of the sequential solid-phase extraction method for simultaneous global and targeted metabolomics analyses of plasma and oral fluid. Such studies will benefit from the systemic, more in-depth characterization of metabolite status, enriched pathway coverage, and faster identification and transition of putative biomarkers from the discovery to the targeted stage. Therefore, my research provided the necessary groundwork for developing and validating universal preparation and analysis workflows, which will permit the execution of pluripotent metabolomics studies.
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identifier: Hundert, Daniel Leibish  (2020) Believing In Oneself: An Analysis of the Views of R. Noson Sternharts of Nemirov on the Enlightenment.  PhD thesis, Concordia University.

abstract:
ABSTRACT
Believing in Oneself: An Analysis of the Views of R. Noson Sternharts of Nemirov on the Enlightenment
Daniel Leibish Hundert, PhD
Concordia University, 2020

	This dissertation will map out a broad and complex picture of the theological universe of R. Noson Sternharts of Nemirov (1780-1844) on the Enlightenment and the Haskalah, as expressed in his magnum opus: Likutei Halachot. The analysis presented here will result in a substantial revision of the scholarly consensus regarding Noson’s views, especially of the Enlightenment and the Haskalah: whereas his approach has been previously understood one-dimensionally, as harsh, obsessively and utterly rejectionist, here it will be shown that his rejection of the Enlightenment is nuanced and needs to be understood within the framework of his theology, which does include a place for the new scientific thinking of the era. In a broader context this study provides a careful analysis of the thinking of a European Jewish believer in the first half of the nineteenth-century confronting the challenges of modernity.
	As the notion of God ascended to the abstract heights of an Aristotelian “unmoved mover,” or receeded into the immutable laws of nature of a Spinozist pantheism, the individual was left bereft of a sense of inherent self worth that is rooted in a living relationship with God. The personal religious experience, the religious sense of quest, came to be seen as outdated, laughable, and simply false. Hence a major aspect of R. Noson’s polemic was the reinstatement of the human being to a position of being valued by God and capable of engaging in relationship with God. This reinstatement is not an abstraction, it must be believed personally: this is called emunah b’atsmo or faith in oneself.


identifier: Yang, Nan  (2020) Contamination in Cryptographic Protocols.  PhD thesis, Concordia University.

abstract: We discuss a foundational issue in multi-prover interactive proofs (MIP) which we call "contamination" by the verifier. We propose a model which accounts for, and controls, verifier contamination, and show that this model does not lose expressive power. A new characterization of zero-knowledge naturally follows. We show the usefulness of this model by constructing a practical MIP for NP where the provers are spatially separated. Finally, we relate our model to the practical problem of e-voting by constructing a functional voter roster based on distributed trust.


identifier: Zareashkezari, Manzarsadat  (2020) Stories of Reading: Are Recollections of Reading Instruction Related to Current Print Exposure?  Masters thesis, Concordia University.

abstract: Children’s reading skills during the early years of schooling are positively correlated to the amount of leisure reading they engage in later in life. It therefore goes to reason that these early experiences with print may impact how individuals later view themselves as “readers.” However, the relationship between adults’ memories of reading during their elementary and high school years and their present-day reading habits has not been systematically examined. Here, I investigated the association between recollections of past reading experiences and reading habits into adulthood among 67 adults. Participants completed an online survey, including three written prompts that asked about their memories of reading during: a) early childhood, b) elementary school, and c) high school. There was also a prompt that asked participants to describe their current reading habits. Participants also completed an Author Recognition Test (ART) to assess their current print exposure, and two questionnaires asking about the frequency of classroom activities during elementary and high school. Results of the Kendall’s Tau correlation showed a significant positive relationship between favourable memories of reading during school years (including those involved in classroom activities), and enthusiastic present-day reading habits. Furthermore, only unfavourable memories of reading during high school were associated with unenthusiastic present-day reading habits. Findings highlight the importance of increasing teachers’ knowledge about the benefits of creating positive memories of reading during school years, and the ways they can create such memories in their classroom by adopting motivational teaching strategies.


identifier: Couillard, Mathieu  (2021) Study and Development of Whispering Gallery Mode Resonators for Technological Applications.  Masters thesis, Concordia University.

abstract: Whispering gallery mode resonators (WGR) are optical cavities with very low loss. This property makes them particularly interesting for many applications including sensors and nonlinear optics. Despite all the research devoted to these cavities, many basic aspects of WGR are not completely understood and many issues still inhibit these technologies from being used in real world applications. This thesis aims to address some of these issues. First, this thesis presents an attempt of a non-destructive techniques to accurately measure the absolute radius and refractive index of a WGR. In order to do so, instrumental techniques were developed to first accurately determine the mode order number without relying on approximations and, second, determine the axial position where the radius is being measured. Perturbations of the modes are then studied using the interactions of a tapered fiber and optically trapped nanoparticle. An earlier experiment demonstrated a frequency shift occurs when the nanoparticle is in proximity of the tapered fiber. This effect was not observed in our experiment. This thesis then reviews the Pound-Drever-Hall technique and describes an implementation using a single board computer for many of the electrical components. Lastly, packaging was developed to improve the robustness of the tapered fiber and reverse the degradation of the Q factor due to adsorbed water on the surface of silica SNAPs. The packaging is robust enough to transport the fiber to different laboratories but cannot withstand the temperatures required to remove the adsorbed water.


identifier: Turan, Devrim  (2021) College level students’ understanding of functions in the context of modelling dynamic situations.  Masters thesis, Concordia University.

abstract:
One of the critical tasks in early mathematical education is teaching the concept of function and its different representations through diverse examples and dynamic tasks. This task is meant to enable students to develop meaningful and powerful constructions between functional concepts and procedures, to conceptualize a function as a generalized process that accepts input and produces output and, therefore, to build essential conceptual and analytical thinking of functions that are necessary to form a covariational conception of function. This is particularly useful for College level students enrolled in Calculus courses who need a strong covariational conception of function to further succeed in mathematics courses.
My thesis reveals that, from a sample group of college level students enrolled in Calculus courses at Concordia University, many participants do not have a strong conceptual or/and analytical thinking of functions that is essential in meaningfully modeling dynamic situations. Majority of students, who have obstacle(s) or/and pseudo-thought(s) or/and misconception(s) due to them having weak analytical/conceptual understanding of functions, do not move flexibly between different representations of functions and fail to view a function as a process that maps values of one variable to values of another variable. Consequently, these students generally do not reason dynamic functional situations covariationally at a higher level. This outcome questions the readiness of Calculus students for subsequent mathematics courses, as well as the effectiveness of prior school curriculum in mathematics education.


identifier: Bouwman, Danya  (2021) Welcome to the Machine: The Impact of News Analytics on High-Frequency Stock Market Dynamics.  Masters thesis, Concordia University.

abstract: I investigate the impact of unscheduled, firm-specific news on high frequency stock market reactions using a five-year sample of intraday news releases and their corresponding Sentiment, Relevance, and Novelty scores generated by the Thomson Reuters News Analytics (TRNA) algorithm. My analysis features one-second interval price and volume data as well as matching trade and quote (TAQ) data for 55 Nasdaq stocks listed on the index between 2011 and 2015 inclusively. I examine cumulative abnormal returns, volumes, and trades, and further employ a quantile regression model that includes measures of news traffic to determine whether machine- readable news can effectively flag short-term trading opportunities. In line with related studies, I find significant increases in abnormal trading activity in the first few minutes surrounding a news release, with volume proving to be more sensitive to the TRNA metrics than returns. Positive news is traded more aggressively than negative news on the knee-jerk, but also experiences sharper reversals in abnormal returns in the hours following. Furthermore, results from the quantile regression analysis appear to confirm that news traffic in the run-up to and at the release time significantly impact abnormal returns. Although my results appear consistent with the hypothesis that trading activity should increase as TRNA thresholds become stricter, simulated holding period returns remain negative, highlighting the many complexities involved in algorithmically trading the news.


identifier: Rosciszewska, Joanna  (2021) Forms and Functions of Prosocial Behavior Moderate the Continuity of Aggression in Early Adolescence.  PhD thesis, Concordia University.

abstract: Typically, measures of aggression are negatively related to measures of prosocial behavior; however, under certain circumstances prosociality may actually promote aggression (Hawley, 2002). A subset of school-aged students may use both behaviors simultaneously to navigate and influence their peer system. Thus, it is imperative to investigate the extent to which their interaction may be associated with promoting or minimizing aggression over time. These associations were investigated in two short-term longitudinal studies of 5th and 6th grade students. Peer nomination procedures were used to assess different forms (e.g., ethic of care and justice) and functions (e.g., proactive, reactive help) of prosocial behavior on changes in physical and relation aggression across a school semester. The results of Study 1 indicate that both types of aggression are stable. Whereas physical aggression declined over a 4-month period, relational aggression increased among girls as well as boys. In line with predictions, students who were initially high on care and justice increased in relational aggression, compared to those scoring low on measures of care and justice. On the other hand, high levels of care and justice were protective against physical aggression. The effects of care were replicated in Study 2 providing compelling evidence that care orientation helps promote relational type of aggression in early adolescence. However, ethic of justice was found to have a buffering effect against relational aggression, contrary to what was observed in Study1. Further, driven by the need to better understand the motivational factors underling prosocial behaviors, proactive and reactive functions of helping were explored and their associations with aggression. Proactive help was unrelated to either type of aggression; on the other hand, reactive help at the beginning of a school semester had a buffering effect on physical aggression two months later. Together, this set of results highlights the importance of taking into account multiple aspects of prosociality to better understand their links with aggression. Understanding factors associated with elevated aggression over time is integral in designing prevention and interventions programs aimed to reduce i


identifier: Razban, Masoud  (2021) Toward Intraluminal Force Monitoring and Automated Insertion in Robotic Endovascular Intervention.  PhD thesis, Concordia University.

abstract:
Endovascular interventions have been broadly embraced in treating and diagnosing vascular and cardiac diseases. The robotic practice of endovascular procedures has significantly reduced radiation exposure of clinicians and improved the precision, stability and controllability of interventional tool motion. Despite improvements in tools and robotic systems, intraprocedural risks of complications including perforation, dissection, embolization, thrombosis, brain lesions, and stroke are still high. Studies pointed out tool-tissue interaction on the arterial wall as the leading cause of complications and the associated post-treatment risks. Clinicians have limited knowledge of intraluminal interactions taking place through the length of endovascular tools during navigation as well as limited control over such interactions. This research proposes a framework for measurement, monitoring, and control of intraluminal contact force (ICF) of endovascular devices. This thesis presents an image-based sensing solution to estimate multiple contact forces (CF) along the catheter/guidewire and delivers an ICF monitoring system during endovascular navigation. It also proposes a semi-automated robotic framework limiting ICF using image-based control methods.
The proposed sensor-less approach employs a numerical finite element simulation of the tool using image-based data. Real-time image segmentation and tracking algorithms are developed to extract tool shape and compute contact deflections and pose data. An FEM model is built using nonlinear beam elements and image-based pose measurements. The model requires tool flexural rigidity distribution as a fixed-parameter input. Accordingly, a set of experiments are performed to measure the equivalent flexural rigidity along the tool using sequential three-point bending tests. To validate the accuracy of contact force estimations, an experimental setup is prepared with separated contact point phantoms allowing direct CF measurements via a F/T sensor. The results show the effectiveness of the proposed approach in accurately estimating multi-point CFs at the side of an interventional tool. In a second study, the proposed force estimation concept is used to implement an image-based intraluminal tool-vessel interaction monitoring system, which has been tested on teleoperated robotic cannulation of aortic arteries in an anthropomorphic phantom. Moreover, this study compares intraluminal CF with the total force exerted on the vascular phantom to highlight the importance of monitoring local tool-tissue interactions. In the experimental setup, a robotic driver system is designed and fabricated based on the methods in conventional manual navigation. The FEM model is updated to consider large axial, bending and shear deformation. Detection and tracking of contacts within the phantom and computation of tool pose are obtained through a real-time imaging algorithm. The proposed method achieved intraluminal monitoring by tracking multi local ICF during procedure and building ICF contour on the phantom arterial wall. Results suggest that high-risk local overloading may happen even when vascular insertion force is low. The image-based method also computes structural stress of the tool in practice. The proposed online tool-tissue monitoring method delivers insight into the intraluminal interactions and is well-suited for clinician visual guidance, robotic control systems, and research tool design.
The final part of the thesis presents a semi-automated robotic insertion framework to control the intraluminal interaction forces under a prescribed safe reference while advancing the navigation procedure. The method uses the proposed image-based force sensing feedback in a velocity-actuated contact force control loop to perform regulated insertion. An automated retraction-reinsertion feature is developed using visual servoing of the tip to relax the excessive forces and extreme deflection caused by friction build-up. The system switches between ICF control and tip visual servoing to advance the navigation. The proposed automated insertion achieved effective control on intraluminal interaction forces during aortic arteries navigation. Experimental study demonstrates superior performance of the automated framework compared to manual teleoperation modes with and without utilizing visual ICF monitoring. Automated ICF control can minimize the risk of complications and enhance the quality of endovascular procedures. Employing ICF as a visual monitoring also improved the task performance compared to traditional teleoperation in both force and motion metrics.


identifier: Pirro, Teresa  (2021) Is and Ought: Mother-Child Disagreements about Facts and Values when Discussing Peer Conflicts.  Masters thesis, Concordia University.

abstract: This study investigated interpersonal disagreements in conversations between mothers and their children with a focus on distinctions between disagreements about facts and values. We aimed to examine: (1) how the frequency and quality of disagreements between mothers and children varied across age and domain of disagreement; and (2) how parenting style was associated with these patterns. The study was based on a sample of 102 mother-child dyads, subdivided in three groups based on the child’s age (i.e., 6 to 7, 10 to 11, or 15 to 16 years). Each dyad discussed two conflictual events that the child had experienced with their peers; disagreements within these conversations were coded. Mothers also completed a measure of parenting style. Results demonstrated that older children had more disagreements with their mothers. In general, dyads had more disagreements about facts rather than values. When disagreements were based on basic-event related facts, the child was more likely to prevail, whereas mothers were more likely to prevail when disagreements were based on values. Parenting styles were not significantly linked to the quantity or quality of mother-child disagreements. These findings shed light on how mother-child interpersonal disagreements in different domains arise and are resolved across childhood and adolescence. Findings are considered in light of epistemological frameworks, and implications for parents are discussed.


identifier: Fuoco, Julia  (2021) It’s All Relative: Sibling and Parent Teaching in Early Childhood.  Masters thesis, Concordia University.

abstract: Research investigating family teaching is limited, and the recent focus on teaching in naturalistic settings has examined sibling-directed teaching when parents do not take an active role. Additionally, the family teaching literature has been widely devoted to studying teaching strategies. Examining conceptual and procedural knowledge provides insight on the ways families co-construct meaning and scaffold learning. The goal of this study was to compare parents’ and siblings’ conceptual and procedural knowledge use during naturalistic teaching episodes in the home. Thirty-seven middle-class families from southwestern Ontario, Canada were observed over two years as they engaged in six 90-minute interaction sessions. The present study examined data from the second time point, when children were four and six years of age. Parental teaching sequences were identified; previously coded sibling teaching sequences were also employed. Parental and sibling teaching sequences were coded for conceptual subcategories (social conventional behavior; game discussions; discussions surrounding language, literacy, and math concepts; and explaining concepts) and procedural knowledge subcategories (game procedures; other procedures). Results demonstrated no significant differences between mothers and fathers in their conceptual and procedural teaching. However, parents taught proportionally more conceptual knowledge than siblings, and siblings taught proportionally more procedural knowledge compared to parents. Parents taught more social conventional behaviors, whereas siblings taught more language, literacy, and math concepts. Siblings also taught more other procedures than parents. Findings surrounding parents’ and siblings’ knowledge use, overall and by subcategory, across context and initiation are further discussed in light of current theory about teaching.


identifier: Asif, Amir, Al-Dulaimi, Ali and Mohammadi, Arash  (2020) Degradation Modeling and Remaining Useful Life Estimation: From Statistical Signal Processing to Deep Learning Models.  PhD thesis, Concordia University.

creator:
Asif, Amir
Al-Dulaimi, Ali
Mohammadi, Arash

abstract:
Aging critical infrastructures and valuable machineries together with recent catastrophic incidents such as the collapse of Morandi bridge, or the Gulf of Mexico oil spill disaster, call for an urgent quest to design advanced and innovative prognostic solutions, and efficiently incorporate multi-sensor streaming data sources for industrial development.  Prognostic health management (PHM) is among the most critical disciplines that employs the advancement of the great interdependency between signal processing and machine learning techniques to form a key enabling technology to cope with maintenance development tasks of complex industrial and safety-critical systems. Recent advancements in predictive analytics have empowered the PHM paradigm to move from the traditional condition-based monitoring solutions and preventive maintenance programs to predictive maintenance to provide an early warning of failure, in several domains ranging from manufacturing and industrial systems to transportation and aerospace. The focus of the PHM is centered on two core dimensions; the first is taking into account the behavior and the evolution over time of a fault once it occurs, while the second one aims at estimating/predicting the remaining useful life (RUL) during which a device can perform its intended function. The first dimension is the degradation that is usually determined by a degradation model derived from measurements of critical parameters of relevance to the system. Developing an accurate model for the degradation process is a primary objective in prognosis and health management. Extensive research has been conducted to develop new theories and methodologies for degradation modeling and to accurately capture the degradation dynamics of a system. However, a unified degradation framework has yet not been developed due to: (i) structural uncertainties in the state dynamics of the system and (ii) the complex nature of the degradation process that is often non-linear and difficult to model statistically. Thus even for a single system, there is no consensus on the best degradation model. In this regard, this thesis tries to bridge this gap by proposing a general model that able to model the true degradation path without having any prior knowledge of the true degradation model of the system. Modeling and analysis of degradation behavior lead us to RUL estimation, which is the second dimension of the PHM and the second part of the thesis. The RUL is the main pillar of preventive maintenance, which is the time a machine is expected to work before requiring repair or replacement.
Effective and accurate RUL estimation can avoid catastrophic failures, maximize operational availability, and consequently reduce maintenance costs. The RUL estimation is, therefore, of paramount importance and has gained significant attention for its importance to improve systems health management in complex fields including automotive, nuclear, chemical, and aerospace industries to name but a few. A vast number of researches related to different approaches to the concept of remaining useful life have been proposed, and they can be divided into three broad categories: (i) Physics-based; (ii) Data-driven, and; (iii) Hybrid approaches (multiple-model). Each category has its own limitations and issues, such as, hardly adapt to different prognostic applications, in the first one, and accuracy degradation issues, in the second one, because of the deviation of the learned models from the real behavior of the system. In addition to hardly sustain good generalization. Our thesis belongs to the third category, as it is the most promising category, in particular, the new hybrid models, on basis of two different architectures of deep neural networks, which have great potentials to tackle complex prognostic issues associated with systems with complex and unknown degradation processes.


identifier: Chen, Chen  (2021) Does watching others eat in videos make you buy? Food eating videos and their relationships to food purchase.  Masters thesis, Concordia University.

abstract:
Young people globally are increasingly watching food eating videos. Researchers do not yet understand why individuals watch these videos when they are eating and what impact they have on the watcher. This study investigates the relationships between food choice motives (specifically mood), attitudes towards the video, attitudes towards the vlogger, purchase intention, food neophobia, and sensitivity to visual food cues by applying the theory of planned behavior (TPB). The study was conducted in two phases: a qualitative content analysis and an experimental design. The content analysis phase analyzed the comments of 16 food eating videos on Chinese social media. It showed that audiences may have different attitudes, consumption patterns and eating habits. Three types of audiences were identified by explorative typology: psychological pleasure seekers, common point seekers, and eating desire eliminators. Based on the content analysis findings, an independent measures design was used to randomly assign participants to two groups (n=269) to answer self-administered online questionnaires. The data was analyzed using descriptive statistics, exploratory factor analysis, confirmatory factor analysis, linear regression, and moderated regression analysis. Results show that audiences’ attitude towards the video is a predictor of purchase intention. Food neophobia moderates the relationships between mood and the viewer’s attitudes towards the video; it also moderates the relationship between the viewer’s attitudes towards the vlogger and purchase intention. Sensitivity to visual food cues is found to have a mild moderating effect on the relationship between the viewer’s attitude towards the vlogger and purchase intention.
This research is different from previous research because it uses the TPB rather than counteractive-control theory, which focuses on audiences’ purchase intention rather than food intake. It also focuses exclusively on mood as a food choice motive. This study’s findings fill the gap between theory and practice and demonstrate that watching food eating videos can impact audiences’ purchase intention. Marketers can use the findings to maximize their profits while policymakers and health associations could establish new guidelines for vloggers to encourage healthy eating habits in their audiences.


identifier: Goubran, Sherif ORCID: https://orcid.org/0000-0002-2365-0351 <https://orcid.org/0000-0002-2365-0351>  (2021) Our Buildings Have Credentials…Now What? A Design-Based Analysis Framework for Reconciling Green Buildings with the Sustainable Development Goals.  PhD thesis, Concordia University.

abstract: Today's definition of sustainable buildings is primarily linked to their environmental performance and hedged on context-free and efficiency-driven standards, certifications, and recognitions. On the other hand, sustainable development requires simultaneous consideration of human and natural systems' needs. Beyond environmental credentials, the study aims to correct this epistemological contradiction by reintegrating sustainable building practices within the broader scope of sustainable development. The study adopts the UN 2030 Agenda as a comprehensive and unifying framework for sustainable development, presenting an opportunity for systemic change towards a sustainable future. The thesis examines the current sustainable real estate and building design approaches and academic debates, analyzing how the prevailing design analysis and assessment frameworks address the Sustainable Development Goals (SDGs). It exposes that the existing body of work is fragmented across different paradigms, showing that the prevailing approaches fail to account for the topic's pluralistic nature and exposing the misalignment between the current building practices and tools and the SDGs' transformative vision on the practical and theoretical levels. Furthermore, the current trends in sustainable real estate point to the broadening of concerns - making our current understanding and practice of sustainability in buildings practically ineffective. Alternatively, and to move beyond the current impasse, the research proposes adopting more complex and value-added analytical instruments that could maintain plurarily and accept opposites' co-existence. The research produces a theoretical framework for distinguishing between the critical and status-quo sustainable design approaches in buildings. The thesis also generates and tests mapping tools and frameworks for critically integrating the SDGs in building projects and analyzing their design approaches. Finally, the thesis examines the coverage, integration and design vision of Canada's most awarded green buildings to the SDGs' topics. While some examples of sustainability innovations emerge, the analysis reveals several gaps and limitations. This thesis contributes to the theory and practice of environmental design within the meta-field of architecture. It expands sustainable building approaches and redefines them as a critical practice for development. The findings and tools can enable the building industry and governmental bodies to accelerate the uptake and implementation of the 2030 Agenda in the built environment.


identifier: McGarvey, Kathleen  (2020) Manipulation of states of light in optical ring resonators.  PhD thesis, Concordia University.

abstract: An optical ring resonator is a fundamental element of an integrated photonic circuit due to its ability to confine optical waves. Composed of a dielectric waveguide closed in a loop, the periodic geometry of the ring allows for the build-up of high-intensity electric fields at particular wavelengths of light known as resonances.  These resonances can be used for applications in fields such as non-linear optics, biosensing, and high-precision spectroscopy.  The intended operation of a ring resonator is often limited by the underlying material dispersion of the ring’s waveguide. To counteract these effects, the dispersion of the waveguide can be designedly engineered via precise geometric patterning of the material. In this work, several dispersion engineering methods are proposed. In particular, condensed matter theories including Bloch’s theorem, the Su-Schrieffer-Heeger model, and synthetic dimensions are applied to the periodic dielectric function of the ring.  Using these principles, photonic analogs of band structures, topologically-protected edge states, coupled degenerate two-level systems, and a synthetic modal dimension in an optical ring resonator will be shown.


identifier: Michaelis-Law, Daniel  (2020) The Calgary School through the lens of Alexis de Tocqueville.  Masters thesis, Concordia University.

abstract: This thesis aims to further expand on the intellectual influence of Tocqueville in the Calgary School’s work. It is aimed at trying to better understand the Calgary School and Alexis de Tocqueville. This thesis tries to address a lack of literature on the Calgary School, there is a lack of literature on them and oftentimes they are dismissed out of hand by left-leaning scholars and critics. This project is not an apology for the Calgary School merely to better understand their ideas and the influences behind them. To accomplish this goal three different themes are used that correspond to the first three chapters of this thesis. The overall common thread or unifying theme used to tie Tocqueville and the Calgary is a critique of the trajectory of liberal democracy, that while critical still supports the basic tenets of liberal democracy. This leads to an understanding that is more subtle, and more generous reading of neoconservative thought in Canada. Categorizations such as neoconservative can in fact be misleading and misrepresentative of the actual thought and ideas of the authors at hand. There are firm philosophical underpinnings to the thought of the Calgary School. Neoconservatism can be perspective that is both sensitive to the values of liberal democracy and critical of the problems inherent with it. While not without its issues, neoconservatism deserves to have its influences more thoroughly investigated.


identifier: Séguin, Frédéric  (2021) A novel method for the analysis of 5-aminoimidazole-4-carboxamide-1-ß-D-ribofuranoside (AICAR) in urine by isotope ratio mass spectrometry for anti-doping purposes.  Masters thesis, Concordia University.

abstract:
In the last 20 years, isotopic ratio mass spectrometry coupled with gas chromatography (GC/C/IRMS) applied to carbon stable isotope (13C/12C) ratios (CSIR) has been a fundamental tool in the field of anti-doping analysis. Some compounds, such as testosterone, can be found in human urine as the result of natural metabolism or exogenous intake, sometimes leaving its carbon isotopic signature as the only proof of an antidoping violation. More recently, the appearance of a new non-steroidal compound named 5-aminoimidazole-4-carboxamide-1-ß-D-ribofuranoside (AICAR) has been of major concern. Experiments made on mice, combined with rumors in the world of sport, has made the compound a suspect for anti-doping authorities. As an intermediate in the purine synthesis, AICAR is also present in urine. The development of a GC/C/IRMS method to distinguish between natural and synthetic AICAR therefore appears necessary, but is not done without issues as AICAR is a non-volatile and unstable molecule at high temperatures. Existing methods use trimethylsilyl (TMS) derivatization, which damages combustion furnaces and adds 9 carbon atoms to the AICAR molecule.
This work therefore proposes a new GC/C/IRMS method that uses acetylation as an alternative route to analyze the CSIR of AICAR for anti-doping purposes. The different issues encountered when developing such method are described as well as the data obtained from its validation and from the analysis of 46 urines samples. A comparison of the results from this work with the existing literature is also made.  The results suggest that the use of CSIR to determine the origin of AICAR in urine is more complex than previously reported.


identifier: Fathi, Vida  (2021) Reinforcement Learning in Linear Quadratic Deep Structured Teams with Performance Guarantee.  Masters thesis, Concordia University.

abstract:
In this thesis, the global convergence of model-based and model-free gradient descent and natural policy gradient descent algorithms is studied for a class of linear quadratic deep structured teams. In such systems, agents are partitioned into a few sub populations wherein the agents in each sub-population are coupled in the dynamics and cost function through a set of linear regressions of the states and actions of all agents. Every agent observes its local state and the linear regressions of states, called
deep states. For a sufficiently small risk factor and/or sufficiently large population, we prove that model-based policy gradient methods globally converge to the optimal solution. Given an arbitrary number of agents, we develop model-free policy gradient and natural policy gradient algorithms for the special case of risk-neutral cost function. The proposed algorithms are scalable with respect to the number of agents due to the fact that the dimension of their policy space is independent of the number of agents in each sub-population. Furthermore, the connection between the model-based and model-free methods is investigated for systems having unknown nonlinear terms with bounded Lipschitz constants. As an extension, the existence of a near-optimal solution in the convex vicinity of initialized controllers obtained from model-based LQR methods is proved. We show these initialized control strategies are derived by solving an algebraic Riccati equation (ARE), obtained by neglecting the nonlinear terms. Finally, we provide convergence guarantees to the optimal solution using a derivative-free policy gradient approach. Simulations confirm the validity of the analytical results.


identifier: Amirkhani, Mahsa  (2021) Bayesian Learning Frameworks for Multivariate Beta Mixture Models.  Masters thesis, Concordia University.

abstract:
Mixture models have been widely used as a statistical learning paradigm in various unsupervised machine learning applications, where labeling a vast amount of data is impractical and costly. They have shown a significant success and encouraging performance in many real-world problems from different fields such as computer vision, information retrieval and pattern recognition. One of the most widely used distributions in mixture models is Gaussian distribution, due to its characteristics, such as its simplicity and fitting capabilities. However, data obtained from some applications could have different properties like non-Gaussian  and asymmetric nature.
In this thesis, we propose multivariate Beta mixture models which offer flexibility, various shapes with promising attributes. These models can be considered as decent alternatives to Gaussian distributions.
We explore multiple Bayesian inference approaches for multivariate Beta mixture models and propose a suitable solution for the problem of estimating parameters using Markov Chain Monte Carlo (MCMC) technique. We exploit Gibbs sampling within Metropolis-Hastings for learning parameters of our finite mixture model. Moreover, a fully Bayesian approach based on birth-death MCMC technique is proposed which simultaneously allows cluster assignments, parameters estimation and the selection of the optimal number of clusters. Finally, we develop a nonparametric Bayesian framework by extending our finite mixture model to infinity using Dirichlet process to tackle the model selection problem. Experimental results obtained from challenging applications (e.g., intrusion detection, medical, etc.) confirm that our proposed frameworks can provide effective solutions comparing to existing alternatives.


identifier: Aceves Bernal, Annele Elmira  (2021) Informality and Formality Practices in Coexistence: Public Markets in Mexico.  Masters thesis, Concordia University.

abstract: Public markets in Mexico and Latin America are important spaces of commercialization and social revitalization that contain a representative set of regional environment (Licona 2014, 142). One intrinsic attribute of public markets is the informal vibe in which they are immersed. Informality has been studied using cases of application such as informal employment (Moser 1978; Crossa 2016) and squatting (Roy 2005, 2009; McFarlane 2012). However, despite being a very relevant epicenter for social dynamics, public markets have not been studied under the light of formality and informality in coexistence. This research asks why do stakeholders in this public markets use both formal and informal practices in their market-related activities. To answer this question three major axes will be explained on which this imbrication happens: Pragmatism- where agents use informality or formality depending on which one provide the greatest benefits or the lowest cost (Loayza 2008, 50), government action or inaction- where informality appears in legal loopholes in ambiguous regulation (Navarrete 2016, 287) or in the poorly enforcement of regulations (Banks et al. 2019, 11), and social networks and culture- Mexican civil society historically has low confidence in institutional agents that enforce and establish the law (Mitofsky 2020). Mainly because of the high number of cases of impunity and corruption (Tronco 2012, 230), promoting in different issues the general acceptance of Non-compliance with the regulation.


identifier: Marcotte, Jess Rowan  (2021) Hybrid Knowing: Preserving Physically and Digitally Entangled Traces in Hybrid Game Design.  PhD thesis, Concordia University.

abstract:
This dissertation represents the written portion of an interdisciplinary research-creation project that explores ways of studying creative practices with a focus on a kind of interactive experience called a hybrid game. It represents a contribution to the field of critical game design research. It builds on research from an extensive range of fields, including queer game design, intersectional feminist theory, critical design, critical game design, game design practice and methods, practice-based research and research-creation research, performance and theatre, live-action roleplay studies, alternative controller studies, autoethnography, and archival studies. From there, this research proposes and uses a methodology for studying the practice of creating interactive experiences that have non-standard, custom physical elements along with digital ones, especially those involving a facilitator. I make the case that autoethnography, though it has some limitations, is a well-suited method for research-creators engaged in design research.

I performed this autoethnographic research through the use of three case studies undertaken over two years. During that time, I used the methodology that I proposed to create records of my own design practice. Using these records, including audio recordings, video recordings, photography, sketches and handwritten notes, a digital journal, and playtesting data, I analyze the process and each project in turn. I argue that in order to avoid self-deception and arguments made only based on designers' memories, it is crucial for the study of design processes to create timely records of practice. Further, I argue that this serves as both valuable data for the designers who do so as it facilitates learning about their own practices, as well as for other game design researchers seeking primary sources.


identifier: Henderson-Chenail (Henderson), Catherine (Kathryn)  (2021) Affects hétérolingues : Écriture latinx et essais de traduction queer pour un public franco-canadien.  Masters thesis, Concordia University.

abstract: Le roman Empanada, a lesbiana story en probaditas, publié en 2012 par l’autrice chicana Anel I. Flores, va à l’encontre de la classification littéraire entre prose et poésie, de la bienséance hétéronormative et du monolinguisme anglo-saxon. Le pan théorique de notre mémoire interroge le rôle de l’affect dans la prise de décisions traductives, défend le projet d’une pratique essayistique de la traduction et aborde la bâtardise en tant que mode performatif et queer d’écriture. Notre cadre théorique s’inspire des écrits d’Adorno, de Sara Ahmed, de Jack Halberstam et de Judith Butler et des exemples précurseurs de Barbara Godard, Carole Maier et Susanne de Lotbinière-Harwood. Le commentaire qui accompagne cette réflexion vient souligner l’hétérolinguisme exacerbé de notre version du texte de Flores et jette un éclairage sur les différentes défaites qui se dissimulent derrière nos choix. Le pan création de notre mémoire consiste en une traduction d’une douzaine de tableaux d’Empanada et en un essai laissant affleurer un espace de création fluctuant au fil des différentes orientations que prend le corps traduisant. Plutôt que de recourir aux concepts de domestication et d’étrangéisation, lesquels sont souvent évoqués lors de la traduction de textes hétérolingues, nous explorons le pouvoir inaugurateur de l’affect dans le tracé de la frontière entre le familier et l’étranger. L’imbrication de l’hétérolinguisme et du queer nous permet de cibler un lectorat franco-canadien non pas monolithique mais éclaté et d’adresser conjointement l’enchevêtrement de langues traditionnellement considérées distinctes, l’oralité en écriture et la lesbianidad mise en scène par Flores.


identifier: Ihou, Koffi Eddy  (2020) Extensions to the Latent Dirichlet Allocation Topic Model Using Flexible Priors.  PhD thesis, Concordia University.

abstract:
Intrinsically, topic models have always their likelihood functions fixed to multinomial
distributions as they operate on count data instead of Gaussian data. As a result,
their performances ultimately depend on the flexibility of the chosen prior distributions
when following the Bayesian paradigm compared to classical approaches such as PLSA
(probabilistic latent semantic analysis), unigrams and mixture of unigrams that do not use
prior information. The standard LDA (latent Dirichlet allocation) topic model operates
with symmetric Dirichlet distribution (as a conjugate prior) which has been found to carry
some limitations due to its independent structure that tends to hinder performance for
instance in topic correlation including positively correlated data processing. Compared to
classical ML estimators, the use of priors ultimately presents another unique advantage of
smoothing out the multinomials while enhancing predictive topic models.
In this thesis, we propose a series of flexible priors such as generalized Dirichlet (GD)
and Beta-Liouville (BL) for our topic models within the collapsed representation, leading
to much improved CVB (collapsed variational Bayes) update equations compared to ones
from the standard LDA. This is because the flexibility of these priors improves significantly
the lower bounds in the corresponding CVB algorithms. We also show the robustness of our
proposed CVB inferences when using simultaneously the BL and GD in hybrid generative-discriminative models
where the generative stage produces good and heterogeneous topic
features that are used in the discriminative stage by powerful classifiers such as SVMs
(support vector machines) as we propose efficient probabilistic kernels to facilitate processing
(classification) of documents based on topic signatures. Doing so, we implicitly cast topic
modeling which is an unsupervised learning method into a supervised learning technique.
Furthermore, due to the complexity of the CVB algorithm (as it requires second order
Taylor expansions) in general, despite its flexibility, we propose a much simpler and tractable
update equation using a MAP (maximum a posteriori) framework with the standard EM
(expectation-maximization) algorithm. As most Bayesian posteriors are not tractable for
complex models, we ultimately propose the MAP-LBLA (latent BL allocation) where we
characterize the contributions of asymmetric BL priors over the symmetric Dirichlet (Dir).
The proposed MAP technique importantly offers a point estimate (mode) with a much
tractable solution. In the MAP, we show that point estimate could be easy to implement
than full Bayesian analysis that integrates over the entire parameter space. The MAP
implicitly exhibits some equivalent relationship with the CVB especially the zero order
approximations CVB0 and its stochastic version SCVB0. The proposed method enhances
performances in information retrieval in text document analysis.
We show that parametric topic models (as they are finite dimensional methods) have a
much smaller hypothesis space and they generally suffer from model selection. We therefore
propose a Bayesian nonparametric (BNP) technique that uses the Hierarchical Dirichlet
process (HDP) as conjugate prior to the document multinomial distributions where the
asymmetric BL serves as a diffuse (probability) base measure that provides the global
atoms (topics) that are shared among documents. The heterogeneity in the topic structure
helps in providing an alternative to model selection because the nonparametric topic model
(which is infinite dimensional with a much bigger hypothesis space) could now prune out
irrelevant topics based on the associated probability masses to only retain the most relevant
ones.
We also show that for large scale applications, stochastic optimizations using natural
gradients of the objective functions have demonstrated significant performances when we
learn rapidly both data and parameters in online fashion (streaming). We use both
predictive likelihood and perplexity as evaluation methods to assess the robustness of our
proposed topic models as we ultimately refer to probability as a way to quantify uncertainty
in our Bayesian framework. We improve object categorization in terms of inferences through
the flexibility of our prior distributions in the collapsed space. We also improve information
retrieval technique with the MAP and the HDP-LBLA topic models while extending the
standard LDA. These two applications present the ultimate capability of enhancing a search
engine based on topic models.


identifier: Donehower, Joanna Kathleen  (2021) Toward a Dramaturgy of Feminist Spatial Curiosity: Urban Performance Creation in Montreal.  PhD thesis, Concordia University.

abstract: My doctoral research in urban performance engages both creative and academic research modalities to explore the performative interactions between performance and its city of situation, putting into practice a spectrum of historical and contemporary techniques for engaging critically and creatively with urban places. Curiocité is an urban theatre and performance dramaturgy oriented toward apprehending and representing—through curious modalities, narratives, and media—the histories, ambiguities, and differential material and social effects of ongoing capitalist processes on urban neighbourhoods. Abattoir de l’est, the first performance event issuing from Curiocité, is a parable situated in Montreal’s deindustrializing and gentrifying east-end district of Hochelaga-Maisonneuve. In the context(s) of this performance research, curiosity delineates an attitude of desire toward the local and the proximate, describing a complex, careful, and eccentric set of experiential and archival techniques (walking, collecting, and assemblage) for apprehending ever-changing urban places, and drawing from a repertoire of curiosity-related aesthetic forms and techniques, among them the curiosity cabinet, popular motion picture media, object theatre, and epic theatrical techniques of defamiliarization toward “as is” narratives and “common sense” discourses of place. A narrative exegesis to my performance research in Hochelaga-Maisonneuve, Toward a Dramaturgy of Feminist Spatial Curiosity: Urban Performance Creation in Montreal responds to and through the following questions: How can curiosity toward place inform urban performance research? What methods and media support a curious approach to performance creation? Tracing the processes of composition for Abattoir de l’est, from scripting through to the siting of the performance event in the urban field, the exegesis asks after the artist’s own siting in these ongoing capitalist processes, demonstrating curiosity as an epistemic stance and set of methods for urban performance creation that would hold onto the ambivalence of the city, while seeking also to embody curiosity in the text through reflective and reflexive returns to the archives and places of performance research. The exegesis includes the full script of Abattoir de l’est, with performances documented through multiple photographs.


identifier: Hosseini, Mirata  (2021) Toward Resilient Building Design in Energy Performance under Climate Change.  PhD thesis, Concordia University.

abstract:
Building energy simulation is commonly used to evaluate the energy performance of buildings to support decisions made at the design stage or to quantify potential energy savings of various strategies for retrofitting existing buildings. However, in many cases, the anticipated performance through simulation output significantly deviates from actual measured data. A major reason for such discrepancy is due to uncertainty in the simulation inputs.
One source of input uncertainty is weather data representing the climate condition. In order to predict the long-term performance of the buildings with energy simulation, modellers commonly use a single Typical Meteorological Year (TMY) weather data file which supposedly represents the climatic conditions. The single weather year file is composed of hourly resolution data from the most 12 representative calendar months of 30 years which are selected based on statistical similarity to long-term weather daily-averaged data. These weather files are synthetically constructed on historical weather data over a long period of time for an array of weather parameters, such as solar radiation, temperature, wind speed and others. The statistical procedure to construct the weather files depends on the weights assigned to these weather parameters. Under current practice, these weighting factors are universally assigned regardless of climatic locations nor the building application. This approach leads to energy performance predictions that deviate from the long-term averages.
Nevertheless, the single weather file ignores the variation in building energy performance resulted from natural weather variation. This source of uncertainty becomes even more critical when the long-term superimposed effect driven by human and anthropogenic factors are added to natural variation. Historical weather data shows that compared to other regions, higher latitudes, including Canada, have been affected more by climate change, and it is expected that this change will be even more in the years to come. Uncertainty due to weather variation and climate change is one of the main reasons for unexpected actual energy performance. Under the changing climate, building's energy performance is expected to change significantly in the northern climates, including Canada.
The current thesis mainly aims to address the two aforementioned issues with novel approaches:
1. Machine learning were deployed to extract the feature importance of the weather parameters in order to assign non-universal weighting factors straightly proportional to their impacts on energy performance of buildings. Weather files constructed with these systematically assigned weighting factors are climatic location and building type dependent. The newly constructed typical meteorological year weather files were applied to two different climatic locations to investigate the representativeness of these new weather files as compared to existing weather files and historical weather data of actual years. The representativeness was indicated in terms of the deviation in predicted energy performance of buildings between using the typical meteorological year weather file and actual historical weather data. The results indicated that typical meteorological year weather file based on the novel approach offers better prediction (with statistical significance) on energy performance for climatic locations with wider temperature range. As a result, the suggested method avoids potential under/oversizing of equipment and promotes energy conservation.
2. General circulation model (GCM) data considering various climate change scenarios based on socio-economic, population, land use, technology, and policies are used to provide information about future climatic condition. However, there are two primary challenges in application of data for building simulation:
i.	Bias in the models: considerable deviation can be found when the historical GCM data is compared to station observed weather data.
ii.	Inadequate resolution: GCM data has daily temporal resolution rather than the hourly resolution required in building energy simulation.
In order to use this data for simulation purposes and better predict future building performance, further processing is conducted. A statistical bias-correction technique, known as the quantile-quantile method, is applied to remove the bias in the data in order to adapt GCMs to a specific location. The study then uses a hybrid classification-regression (K-Nearest Neighbour – Random Forest) machine learning algorithm to downscale the bias-corrected GCM data to generate future weather data at an hourly resolution for building energy simulation. In this case, the hybrid model is structured as a combined model, where a classification model serves as the main model together with an auxiliary regression model for cases when data is beyond the range of observed values. The proposed workflow uses observed weather data to determine similar weather patterns from historical data and uses it to generate future weather data, contrary to previous studies, which use artificially generated data. However, in cases where the future GCM data showed temperatures ranging outside of the observed data, the study applied a trained regression model to generate hourly weather data. The current study suggests a workflow that can be applied to global and regional models data to generate future weather files year by year for building simulation under various scenarios and, consequently, extreme weather characteristics are preserved for extreme or reliability analysis and design optimization.
In addition, a novel method is introduced to find building design solutions under uncertainty of weather variation and climate change. The design options are architectural and envelop features at different levels. A full factorial design of experiment is used for large-scale simulations and training deep neural network surrogate models to assess energy performance of design alternatives under multiple future years under various climate change scenarios. The method with application of a novel performance indicator is applied to explore design space and find the design solutions that most probably contribute to meet building energy performance targets over the project's lifespan.
This workflow takes into account the effect of weather variation under various climate change scenarios and suggests several design solutions that can be offered to stakeholders, architects, engineers, and third-parties including insurance companies. This way, design alternatives can be compared, and designs with a higher probability of success can be selected as a final solution. In addition, policy-makers can use the results and the suggested workflow to adopt and update national and provincial building energy codes such as National Energy Codes of Canada for Buildings (NECB) in line with the national policies following the Paris climate change agreement.


identifier: Shaghaghian, Sana  (2021) Effervescent Atomization through Circular and Elliptical Nozzles.  Masters thesis, Concordia University.

abstract:
Effervescent atomization in quiescent air and in a subsonic crossflow are experimentally studied. The spray angle of an effervescent atomizer with an elliptical orifice is measured by employing the shadowgraph technique. Spray images were captured from both the minor and major axis views. The gas-liquid mass flow rate ratio (GLR) is in the range of 0.55-2.55 %.  It is found that an increase in the aeration level results in an increase in the spray angle from both minor and major axis views. The results indicate that the spray angle from the minor axis view is wider than that from the major axis view and the difference increases as GLR rises.
Furthermore, the effervescent atomization in a gaseous crossflow is studied using circular and elliptical orifices with aspect ratios of 1, 3, and 0.3. Gas-liquid mass flow rate ratio varies between (0-7%) and liquid-air momentum flux ratio,q, is in the range of 2-23. The high-speed shadowgraph technique and image processing were utilized to visualize the spray trajectory and measure the spray penetration height. Moreover, an empirical correlation is developed as a function of GLR, q, aspect ratio and downstream location. Additionally, the laser diffraction technique is employed to analyze the spray droplet size distribution in a crossflow.


identifier: Ruivivar, June ORCID: https://orcid.org/0000-0003-3471-2084 <https://orcid.org/0000-0003-3471-2084>  (2020) Sociolinguistic Agency in the Learning and Teaching of Regional Variation: Revisiting Pedagogical Norms.  PhD thesis, Concordia University.

abstract:
Pedagogical norms for teaching regional varieties of a target language suggest teaching features that are widely used and valued by the language community, and that support overall linguistic development. This dissertation considers the place of sociolinguistic agency, or learners’ willingness to adopt local linguistic conventions, in this pedagogical norm. It consists of three studies investigating social and affective challenges in the acquisition of features typical of Quebec French, and exploring potential pedagogical solutions to these challenges.
Study One compared native and near-native speakers’ use and understanding of the -tu question particle, a typical QF vernacular feature. Ten dyads consisting of native and near-native speakers completed tasks in casual, semi-controlled, and controlled situations, and a short interview probing their awareness and understanding of QF question variation. Despite having higher metalinguistic awareness, near-native speakers significantly underused -tu compared to native speakers. They tended to favour -tu in lexicalized expressions and slightly overused it in controlled situations.
Study Two investigated the effects of engagement and social networks on sociolinguistic performance. Twenty-one advanced QF learners completed a social network questionnaire and a sociolinguistic interview, which provided data on engagement and sociolinguistic performance. Sociolinguistic performance varied according to type of feature, engagement, and satisfaction with network support. Use of informal features (first-person on and ne deletion) correlated positively with high engagement. The stigmatized colloquial vernacular -tu was virtually absent, and the non-stigmatizednon-colloquial vernacular, subject doubling, correlated with social network satisfaction. Perceptions of QF and attitudes towards the QF community also appeared to play a role.
Study Three presents the theoretical framework, design, and methodology for a classroom study examining the effects of concept-based instruction on learners’ understanding, appropriateness judgments, and emerging sociolinguistic agency. The study illustrates how sociolinguistic agency might be addressed in the classroom and evaluated as a pedagogical outcome. Drawing on these studies, the thesis proposes adding an agentive criterion to the pedagogical norm. This criterion considers learners’ identities, attitudes, and perceptions of the regional variety in deciding which features to teach. It offers suggestions for developing and applying the agentive criterion and broader implications for the teaching and study of sociolinguistic variation.


identifier: Baird, Haley  (2021) Weight Shifting; An Ethnography of Contact Improvisation.  Masters thesis, Concordia University.

abstract: This thesis reflects on ethnographic research of the improvised dance form, contact improvisation. This research addresses the ways in which dancers of contact improvisation navigate the bourgeoning conversation around consent in the context of their practice. In the past several years, consent has become an increasingly pressing concern in the form, and has resulted in the fashioning of guidelines, workshops, and demonstrations meant to address the practice of consent. Based on participant observation and interviews across the San Francisco Bay Area of California (US), Montreal, Quebec (CAN), and various online platforms, this ethnographic study explores some salient questions which dancers seek to address in the context of their dance practice. Contact improvisation historically reflects a strong attachment to ideals of egalitarianism and non-codification. It has frequently been addressed as a practice in which dancers experiment with a certain ‘blurring’ between bodies, states of disorientation, and an improvisational ethos of unpredictability. Thus, it is a particularly challenging and potentially creative venue for thinking about the politics of consent. This thesis does not attempt to give an exhaustive reading of the situation, nor to prescribe a way forward. Rather, this research focuses on several key tensions between contact improvisation and consent. Among them, this work addresses how the relationship of contact improvisation to constraints and to “flow” might need to be rethought in the context of making the practice more consensual.


identifier: Turan, Devrim  (2021) College level students’ understanding of functions in the context of modelling dynamic situations.  Masters thesis, Concordia University.

abstract:
One of the critical tasks in early mathematical education is teaching the concept of function and its different representations through diverse examples and dynamic tasks. This task is meant to enable students to develop meaningful and powerful constructions between functional concepts and procedures, to conceptualize a function as a generalized process that accepts input and produces output and, therefore, to build essential conceptual and analytical thinking of functions that are necessary to form a covariational conception of function. This is particularly useful for College level students enrolled in Calculus courses who need a strong covariational conception of function to further succeed in mathematics courses.
My thesis reveals that, from a sample group of college level students enrolled in Calculus courses at Concordia University, many participants do not have a strong conceptual or/and analytical thinking of functions that is essential in meaningfully modeling dynamic situations. Majority of students, who have obstacle(s) or/and pseudo-thought(s) or/and misconception(s) due to them having weak analytical/conceptual understanding of functions, do not move flexibly between different representations of functions and fail to view a function as a process that maps values of one variable to values of another variable. Consequently, these students generally do not reason dynamic functional situations covariationally at a higher level. This outcome questions the readiness of Calculus students for subsequent mathematics courses, as well as the effectiveness of prior school curriculum in mathematics education.