identifier: Ibn Abbas, Abdullah  (2021) Power-Proportional Optical Links.  PhD thesis, Concordia University.

title: Power-Proportional Optical Links

abstract:
The continuous increase in data transfer rate in short-reach links, such as chip-to-chip and between servers within a data-center, demands high-speed links. As power efficiency becomes ever more important in these links, power-efficient optical links need to be designed.
Power efficiency in a link can be achieved by enabling power-proportional communication over the serial link. In power-proportional links, the power dissipated by a link is proportional to the amount of data communicated. Normally, data-rate demand is not constant, and the peak data-rate is not required all the time. If a link is not adapted according to the data-rate demand, there will be a fixed power dissipation, and the power efficiency of the link will degrade during the sub-maximal link utilization. Adapting links to real-time data-rate requirements reduces power dissipation. Power proportionality is achieved by scaling the power of the serial link linearly with the link utilization, and techniques such as variable data-rate and burst-mode can be adopted for this purpose. Links whose data rate (and hence power dissipation) can be varied in response to system demands are proposed in this work.
Past works have presented rapidly reconfigurable bandwidth in variable data-rate receivers, allowing lower power dissipation for lower data-rate operation. However, maintaining synchronization during reconfiguration was not possible since previous approaches have introduced changes in front-end delay when they are reconfigured. This work presents a technique that allows rapid bandwidth adjustment while maintaining a near-constant delay through the receiver suitable for a power-scalable variable data-rate optical link. Measurements of a fabricated integrated circuit (IC) show nearly constant energy per bit across a 2× variation in data rate while introducing less than 10 % of a unit interval (UI) of delay variation.
 With continuously increasing data communication in data-centers, parallel optical links with ever-increasing per-lane data rates are being used to meet overall throughput demands. Simultaneously, power efficiency is becoming increasingly important for these links since they do not transmit useful data all the time. The burst-mode solution for vertical-cavity surface-emitting laser (VCSEL)-based point-to-point communication can be used to improve links’ energy efficiency during low link activity. The burst-mode technique for VCSEL-based links has not yet been deployed commercially. Past works have presented burst-mode solutions for single-channel receivers, allowing lower power dissipation during low link activity and solutions for fast activation of the receivers. However, this work presents a novel technique that allows rapid activation of a front-end and fast locking of a clock-and-data-recovery (CDR) for a multi-channel parallel link, utilizing opportunities arising from the parallel nature of many VCSEL-based links. The idea has been demonstrated through electrical and optical measurements of a fabricated IC at 10 Gbps, which show fast data detection and activation of the circuitry within 49 UIs while allowing the front-end to achieve better energy efficiency during low link activity. Simulation results are also presented in support of the proposed technique which allows the CDR to lock within 26 UIs from when it is powered on.


identifier: Chan, Janan  (2021) Demonstrations.  Masters thesis, Concordia University.

title: Demonstrations

type: Thesis NonPeerReviewed

abstract: “Demonstrations” is a collection of six short stories which follow protagonist James Kou, a young, middle-class, Hong Kong Chinese-Canadian immigrant studying English literature in Lennoxville, Québec, and later, returning to his birth place of Hong Kong, as he navigates the multiple facets of his personality and begins to understand who he is and where he comes from. These stories explore issues of internal and external racism, familial relations, the rediscovery of culture, language, ancestry, place, and redemption in the form of restorative relationships. The settings of Lennoxville, a majority white and rural area in Québec, and Hong Kong, a majority Chinese, former British colony, reflect the complications of identity exemplified by James. The historical moment of spring and summer 2019 in which majority of these stories take place, as well, imbues James’s visit with an added significance, as it is in this year China attempts to pass an extradition bill which allows detainment of Hong Kong citizens or citizens from other territories such as Taiwan who are deemed dissidents or criminals. The fear however is that such power would be used to suppress political dissent; the proposed bill as of summer 2019 is another example of China’s encroachment upon Hong Kong, an island which is and is not a part of China. Hong Kong in the summer of 2019 saw some of the largest pro-democracy demonstrations yet.


identifier: Ghasemi, Mahsa  (2021) Evaluation of Physical and Chemical Parameters Effects on Different Ozone Monitoring Technologies.  Masters thesis, Concordia University.

abstract:
Since most people spend about 90 percent of their time indoors, having good indoor air quality plays a significant role in human health. Based on EPA studies, indoor air pollution is among the top five environmental health risks. Ozone is considered as one of the typical indoor air contaminants. Air cleaners are one of the indoor sources of ozone production applied for the deodorization and disinfection of air and other indoor sources that release ozone, including printers and photocopiers. Therefore, reliable detection of ozone, especially in low concentrations using sensitive and accurate ozone monitoring technologies, is very noticeable and its market demand is on the rise. However, these detecting technologies suffer from positive or negative interferences from other chemical compounds which exist in the desired environment. Also, humidity and temperature changes can affect indoor ozone levels and ozone monitoring technologies performance.
 In this research, different environmental physical parameters effects like air velocity, airflow direction, and humidity on the performance of ozone monitoring technologies were evaluated in a full duct and small-scale environmental chamber. Also, we examined the responses of these monitoring instruments in the presence of some interfering compounds, including Acetone, Toluene, and Ethanol, using a small-scale chamber at 50% RH and dry condition (0.01%).
The results demonstrated that different airflow rates and airflow directions had a negligible effect on the UV sensors response. While electrochemical and metal oxide sensors outputs were remarkably overestimated with increasing airflow rate. This increase was more evident for electrochemical and metal oxide sensors when placed perpendicular and parallel to the airflow, respectively. Furthermore, the responses of 211-2B, Teledyne, POM and BW experienced a positive interference with rapid humidity variations from 30% to about 80% and a negative bias from 80% to 30% RH. In contrast, BW Solo behaved oppositely. It was difficult to follow the metal oxide changing trend with humidity variations because of the instrument time interval (minimum 10 min). In the absence of ozone, Ethanol caused a slight negative interference to the 211-2B sensor in humid (50%) and dry air (0.01%) and a significant negative bias to Teledyne at 50% RH. 211-2B sensor did not respond to acetone at 50% RH, but it experienced a positive bias in dry air. A considerable positive interference was observed in Teledyne reading at 50% RH. Toluene led to a slight positive interference in 211-2B response in humid and dry conditions. BW Solo and ECO Sensor in the presence of these VOC compounds were consistently showing zero concentration.


identifier: Faust, Rachel  (2021) Group Work at the College Level: a Case Study.  Masters thesis, Concordia University.

abstract:
Research problem:
This study explores the use of group work across various academic disciplines at the college level in Quebec, with the intent of making recommendations on ways to improve its design and implementation.

Research Questions:
1. What practices do college teachers use in implementing group work?
2. What do college teachers perceive as the benefits of group work?
3. What challenges do college teachers face in implementing group work?
4. How do college teachers address the challenges they face in implementing group work? What additional mechanisms could college teachers put in place for an effective implementation of group work?

Literature Review:
The literature review describes the small-group learning approaches most represented in the literature on postsecondary education, namely: cooperative learning, collaborative learning and problem-based learning. The benefits of group work for both students and instructors are presented, as well as the common problems that can arise from group work and possible solutions.

Method:
This qualitative study uses the collective case study methodology. Six cases involving a total of nine instructors are presented. All participants teach at the same Quebec college and were recruited by snowball sampling at the research site. The participants were selected on the basis of their teaching discipline, as well as the type of group work they implement. The data were obtained through semi-structured interviews and were analyzed using a thematic analysis approach.

Results and Conclusions:
The participants implement group work in two distinct ways: in-class, active learning, activities; and graded projects. The following student benefits were identified: students learn effectively; they are engaged; group work sets a positive classroom environment; and simulates real-life situations. Benefits for teachers include: an enhanced monitoring of student’s progress; a reduced grading workload; intrinsic rewards; and a dynamic classroom. Five main challenges were identified: friends tend to work with friends; social loafing; interpersonal difficulties; external pressures; and difficulties assessing individual contribution in group projects. To alleviate difficulties related to in-class activities, the participants can: change the groups frequently; assign specific roles; actively work on setting a positive classroom environment; clearly communicate the learning objectives; and build in an element of competitivity. For group projects, the participants can: discuss the relevance of teams in the workplace; dedicate class time to the group projects; include project milestones; minimize the value of group grades; and use peer-evaluations. The literature further suggests that for in-class activities, the level of difficulty, timing, and variety of the activities are key elements to consider, and that instructors can call on an individual student to present. For group projects, teachers can: favour criterion-based group formation; train students in developing teamwork skills; assign specific roles to students; and ask for progress reports.

The implications of this study are that faculty development initiatives on group work should not be discipline-specific, and can focus on: implementing strategies to reduce social loafing in group projects; training instructors to explicitly teach their students about teamwork skills; and designing activities so that they best reproduce real-life situations.

Because this research is exploratory in nature, there are too few participants to represent the larger population of Quebec college instructors. Another limitation of this study is the absence of representation of group work in technical programs.

Future research could examine group work from the perspective of college students, the barriers to implementing group work in the Quebec collegial system, the implementation of group work online in the context of the COVID-19 pandemic, as well as, post-pandemic, how the instructors’ experiences implementing group work online will have influenced their approaches to group work upon their return in the physical classroom.


identifier: Mills, Patrick  (2021) Flux Reconstruction as a Direct Method for Near-Field Computational Aeroacoustics.  Masters thesis, Concordia University.

abstract:
The noise produced from commercial aviation is detrimental and strictly regulated at an international level. To satisfy stringent forthcoming noise reduction requirements, current industry standard, lower order aeroacoustic methods used to approximate acoustic fields must be replaced with high-order methods that can more accurately compute the acoustic field, providing invaluable insight into noise generation and potential design optimization processes. In this thesis, the accuracy and performance of high-order numerical methods, as applied in the scope of computational aeroacoustics, are evaluated. Specifically, the high-order flux reconstruction method’s ability to directly compute acoustic fields is assessed. The field of computational aeroacoustics is intrinsically dissimilar to the field of computational fluid dynamics and thus contains highly distinctive numerical challenges. Several verification studies are performed, for a range of polynomial orders, each addressing an individual numerical challenge. It is shown that the high order flux reconstruction method sufficiently resolves each of these numerical
challenges, with higher order polynomials providing more accurate and efficient results on a per degree of freedom basis. The high order flux reconstruction method’s proficiency for direct computation of
near-field acoustics is validated by performing simulations of flow over a cylinder and a deep cavity and comparing the results against experimental data. Finally, the performance of the high-order flux
reconstruction method in industrial applications is assessed by directly computing the acoustic field produced by a NACA0012 airfoil at varying angles of attack.


identifier: Thiel, Stuart ORCID: https://orcid.org/0000-0002-2172-3916 <https://orcid.org/0000-0002-2172-3916>  (2021) The Diverting Fast Radix Algorithm.  PhD thesis, Concordia University.

title: The Diverting Fast Radix Algorithm

abstract:
Radix sort is a classical algorithm to sort $N$ records with integer keys. The keys are represented using digits of a radix. The classical algorithm executes a pass through the records to count the frequency of each digit to determine the digit’s bucket size, and then a pass to deal the records to the corresponding bucket. The algorithm may proceed from the most significant digit to the least significant, or from the least significant digit to the most significant.

This thesis presents the Fast Radix and the Diverting Fast Radix algorithms, which replace
all but one count pass with estimation of bucket sizes and correction of overflow, and may,
in addition, divert to another sorting algorithm such as insertion sort when the subproblem
size is below a threshold.

Extensive performance experiments compare the implementations of the two algorithms against the native std::sort in the C++ Standard Library, radix sort, and RADULS2, which is currently considered the fastest radix sort available.

We develop a mathematical model of the average-case performance, when keys have a uniform distribution of digits, that support the observed performance improvements. The modeling demonstrates that the costs of estimation and correction quickly approach zero, falling under 5\% of the costs of traditional counting for $N$ as low as 11100. The modeling also provides a formula to calculate the thresholds for diversion that conform to the experimental results.

Our focus is on algorithms, so our implementation is fixed-digit, single-threaded and avoids optimizations such as parallelism, cache, translation lookaside buffer (TLB), or the specific input distribution, which are utilised by RADULS2. Nevertheless, Diverting Fast Radix is more than twice as fast as std::sort on inputs of size up to one billion (and beyond), and approximately 10\% faster than RADULS2 for one million records (even faster on smaller inputs). It is notable that the compiled code size of Diverting Fast Radix is two orders of magnitude smaller than RADULS2.


identifier: Murphy, Christian  (2021) Generation of Video Game Production Quality Face Textures.  Masters thesis, Concordia University.

abstract: Manually creating realistic, digital human heads is a difficult and time-consuming task forartists. While 3D scanners and photogrammetry allow for quick and automatic reconstruction of heads, finding an actor who fits specific character appearance descriptions can bedifficult.  Moreover, modern open-world video games feature several thousands of characters that cannot realistically all be cast and scanned.  Therefore, researchers are investigating generative models to create 3D head shapes which fit a specific character appearance description. While current methods can generate believable head shapes quite well, generating a corresponding high-resolution, high-quality, production level texture which respects the character’s appearance description has been a major challenge.This work presents methods which combine to generate synthetic face textures at the video game production quality level.  Production quality face textures have the following constraints: (i) game artists control the generative process by providing precise appearance attributes, the face shape, and the character’s age and gender, (ii) the texture must be at least 4096×4096resolution, and (iii) the texture must be in bidirectional reflectance distribution function parameters (diffuse albedo, roughness, specular albedo) for raytraced rendering under different lighting and viewing conditions.The proposed methods build upon earlier deep learning approaches addressing similar problems. Several key additions to these methods have been created to be able to use them in this context, specifically for providing easy artist controls and to work with limited training data. The implementation results show that in spite of training with a limited amount of training data, just over 100 samples, the machine learning model produces realistic textures which comply to a diverse range of skin, hair, lip and iris colors specified through a novel,yet intuitive, description format and augmentation thereof.


identifier: Khadivar, Hamed ORCID: https://orcid.org/0000-0002-8285-3538 <https://orcid.org/0000-0002-8285-3538>  (2021) Three Essays on Informed Trading.  PhD thesis, Concordia University.

title: Three Essays on Informed Trading

abstract:
How pervasive is informed trading around takeover rumors? This dissertation tackles this research question from three different following aspects.
First, we examine insider trading surrounding takeover rumors in a sample of publicly traded U.S. firms. We find that insider net-purchases increase within the year prior to the first publication of a takeover rumor, particularly when rumor articles are either accurate (lead to a takeover announcement) or informative (provide substantial justification for the rumor’s publication). Moreover, we find abnormal insider trading to be a significant predictor of takeover announcements occurring within the following year. Finally, trading patterns differ between different types of insiders in both the pre- and post-rumor periods.
Second, we examine the possibility of informed institutional trading around takeover rumors. We find that pension plan sponsors and money managers are net-buyers in firms which will become subject to takeover speculation within the following seven days. This activity is significant in predicting which rumored firms will eventually receive takeover bids. Furthermore, we find that institutions on average reverse their trades and engage in significant selling on and after the rumor date, even in those firms which will become subject to a takeover announcement.
Third, we investigate and quantify the pervasiveness of informed trading in the equity options of rumored takeover targets. We find that the volume of options traded is abnormally high over the 5-day pre-rumor period, primarily due to the number of out-of-the-money call options traded. In addition, the direction of option trades prior to takeover rumors predicts forthcoming takeover announcements and rumor date returns. Identifying suspicious trades, we find evidence of individuals trading on knowledge of takeover rumor candidacy in the options market. Our results further indicate that informed traders prefer the options market to the equity market.


identifier: Runge, Jason  (2021) Short-term forecasting for the electrical demand of Heating, Ventilation, and Air Conditioning systems.  PhD thesis, Concordia University.

abstract:
The heating, ventilation, and air conditioning systems (HVAC) of large scale commercial and institutional buildings can have significant contributions to the buildings overall electric demand. During periods of peak demand, utilities are faced with a challenge of balancing supply and demand while the system is under stress. As such, utility companies began to operate demand response programs for large scale consumers. Participation in such programs requires the participant to shift their electric demand to off-peak hours in exchange for monetary compensation. In such a context, it is beneficial for large scale commercial and institutional buildings to participate in such programs. In order to effectively plan demand response based strategies, building energy managers and operators require accurate tools for the short-term forecasting of large scale components and systems within the building. This thesis contributes to the field of demand response research by proposing a method for the short-term forecasting for the electric demand of an HVAC system in an institutional building.

Two machine learning based approaches are proposed in this work: a component method and a system based method. The component-level approach forecasts the electric demand of a component within the HVAC system (e.g. air supply fans) using an autoregressive neural network coupled with a physics based equation. The system-level approach uses deep learning models to forecast the overall electric demand of the HVAC system through forecasting the electric demand of the primary and secondary system. Both approaches leverage available data from the building automation system (BAS) without the need for additional sensors. The system based forecasting method is validated through a case study for a single building with two data sources: measurement data obtained from the BAS and from an eQuest simulation of the building. The building used as the case study for the work herein consists of the Genomic building of Concordia University Loyola campus.


identifier: Bani-Sadr, Salman  (2021) Indigenous Research within the Discipline of Geography: An evaluation of three decades of graduate thesis research in Canada.  Masters thesis, Concordia University.

abstract:
This study utilizes a mixed methods approach to evaluate graduate thesis research in Geography departments across Canadian universities on topics involving Indigenous issues/peoples.
Graduate theses considered in the study include masters and doctoral level theses completed in the Geography programs of 22 Canadian universities between 1989 and 2018. The evaluation is intended as a tool or proxy for tracking changes within the discipline of Geography with respect to the respectful engagement of Indigenous peoples. The focus on graduate thesis research is premised on the idea that graduate student training is reflective of discourses and directions that are current within the overall discipline while also shedding light on the formation of the next generation of scholars. The evaluation involved a scoping method which identified 306 graduate theses (201 Masters theses; 105 doctoral theses) through a keyword search of thesis titles and abstracts in ProQuest and the Theses Canada Portal of the Library and Archives Canada (LAC). Findings revealed an increase over time in research topics that involved/impacted Indigenous peoples. Attention to climate change and food security has increasingly dominated as a research theme over the past decade. Qualitative analysis of the theses was conducted based on an assessment of four indicators: 1) acknowledgement of Indigenous participants and communities; 2) inclusion of traditional Indigenous knowledge; 3) application of participatory methods; and 4) benefits of research to the community. Findings reveal a positive trend for each of the indicators over time. However, much remains to be done to advance decolonization within the discipline.


identifier: Poirier, Marilyne  (2021) Changed Ocean Optical Properties: How Shallower Sunlight Absorption impacts Earth’s Surface Energy Budget.  Masters thesis, Concordia University.

abstract: This study investigates the variations in the last decades of underwater sunlight attenuation coefficient (Kd) and its forcing (W/m2¬) on the Earth’s surface heat budget. It first compares the trends of essential climate variables Kd and sea surface temperature (SST) to gauge their connection. To estimate an equivalent global forcing, it also finds the variation of radiant heating rate (RHR) profiles under the ocean surface. The trends over a different period (14 to 30 years) for Kd, SST and diurnal SST (DSST) were extracted using the statistical Seasonal Mann-Kendal test, from remote sensing datasets available respectively on ESA OC-CCI, NOAA and REMSS public FTP servers. The results were geographically compared on 360°x180° gridded maps. They were used to estimate global linear regressions of their correlation coefficients. A positive correlation of 0.38 between Kd and SST was found. This result highlights the relevance to investigate the weight of the fate of irradiance decay on the surface heat budget. Using results of Kd trends over the 18-year period, changed incoming solar radiation (I0) decay in the upper 50 meters, and associated changed RHR profiles, it was possible to map the critical depth (Zcrit) at which the (1998) and (2017) RHR curves crossed path. A slightly better negative correlation of -0.42 was found between SST and Zcrit. The latter was used to calculate and map the theorical forcing on the air-sea interface attributed to ocean color changes. Averaged over the Earth’s surface, the forcing is 0.33 W/m2. This order of magnitude compares to the 3.1 W/m2 attributed to greenhouse gases (GHG) forcing. It suggests that the optically responsive aquatic components accumulated into the oceans may significantly drive the surface energy transfer by retaining the solar irradiance closer to the surface. It is recommended to further the study by including Kd in an OAGCM to account for the feedback of the four main fluxes (shortwave, longwave, latent, and sensible heat) composing the budget. The weighting of the forcing attributed to Kd in the budget will improve the significance of the result. Further investigation toward the management of Shortwave (SW), the black carbon (BC) and the ocean color are also recommended. Solutions against anthropogenic warming are proposed, such as the mixing enhancement of stratified waters.


identifier: Drury, Amanda  (2021) Navigating Technology-Enabled Mindfulness Practices in and Outside of the Classroom: A Curriculum for Teachers.  Masters thesis, Concordia University.

abstract:
Mindfulness has emerged as a promising approach to promote relief in instances of adversity, reduce stress and improve children’s overall wellbeing when properly incorporated in a classroom setting. With the increase in use of technology for online and remote learning, the elaboration of a technology-enabled mindfulness curriculum for teachers and educators is of the upmost importance. The following curriculum has been created to introduce technology-enabled mindfulness practices and explore the current techniques which have been found to be beneficial for use with both neurotypical and neurodivergent children. Through a systematic search and in-depth review of the literature via diverse research databases, the most appropriate practices for teaching mindfulness to children aged 6 to 12 in a school setting were compiled and organized into ten distinct lessons. Lesson plans included in this curriculum feature the central components of mindfulness practices and explicitly demonstrate how these practices can be adapted and applied to be suitable for use online by teachers and educators. This curriculum can serve as a basis for future research conducted on practical ways of integrating alternative methods of delivery in school settings, specifically in terms of technology-enabled mindfulness practices.
Keywords: child, curriculum, mindfulness, technology, COVID-19


identifier: Hooshiar, Amir ORCID: https://orcid.org/0000-0002-9036-5331 <https://orcid.org/0000-0002-9036-5331>  (2021) Image-Based Force Estimation and Haptic Rendering For Robot-Assisted Cardiovascular Intervention.  PhD thesis, Concordia University.

abstract: Clinical studies have indicated that the loss of haptic perception is the prime limitation of robot-assisted cardiovascular intervention technology, hindering its global adoption. It causes compromised situational awareness for the surgeon during the intervention and may lead to health risks for the patients. This doctoral research was aimed at developing technology for addressing the limitation of the robot-assisted intervention technology in the provision of haptic feedback. The literature review showed that sensor-free force estimation (haptic cue) on endovascular devices, intuitive surgeon interface design, and haptic rendering within the surgeon interface were the major knowledge gaps. For sensor-free force estimation, first, an image-based force estimation methods based on inverse finite-element methods (iFEM) was developed and validated. Next, to address the limitation of the iFEM method in real-time performance, an inverse Cosserat rod model (iCORD) with a computationally efficient solution for endovascular devices was developed and validated. Afterward, the iCORD was adopted for analytical tip force estimation on steerable catheters. The experimental studies confirmed the accuracy and real-time performance of the iCORD for sensor-free force estimation. Afterward, a wearable drift-free rotation measurement device (MiCarp) was developed to facilitate the design of an intuitive surgeon interface by decoupling the rotation measurement from the insertion measurement. The validation studies showed that MiCarp had a superior performance for spatial rotation measurement compared to other modalities. In the end, a novel haptic feedback system based on smart magnetoelastic elastomers was developed, analytically modeled, and experimentally validated. The proposed haptics-enabled surgeon module had an unbounded workspace for interventional tasks and provided an intuitive interface. Experimental validation, at component and system levels, confirmed the usability of the proposed methods for robot-assisted intervention systems.


identifier: AbdelRahman, Belal Ali AbdelHafeez  (2021) Monotonic and Cyclic Behaviour of Reinforced Concrete-Masonry Shear Wall Boundary Elements.  PhD thesis, Concordia University.

abstract:
As a seismic force-resisting system (SFRS), reinforced masonry shear walls with masonry boundary elements (RMSW+BEs) were found to achieve enhanced strength, stability, and ductility levels compared to rectangular RMSWs. The seismic design of RMSW+BEs necessitates reliable experimental and analytical investigations of their reinforced masonry boundary elements (RMBEs). The axial monotonic and cyclic stress-strain curves of RMBEs are essential to predict the lateral cyclic response of RMSW+BEs. This research aims to investigate, experimentally and analytically, the axial monotonic and cyclic behaviour of RMBEs built with C-shape masonry blocks. Moreover, this research proposes monotonic and cyclic stress-strain models for unconfined and confined RMBEs subjected to axial compression loading. Furthermore, a numerical study was performed to assess the sensitivity of the nonlinear seismic response of RMSW+BEs to various wall configurations and design parameters.
  This research’s experimental work involved investigating various parameters affecting the compressive strength of fully grouted concrete masonry prisms and the axial monotonic and cyclic behaviour of RMBEs. Forty-two masonry prisms and 69 RMBEs were tested. The studied parameters were the vertical reinforcement ratio, the confinement ratio, the cross-section geometry (i.e., square vs. rectangular RMBEs), the masonry bonding pattern, pre-wetting of dry RMBEs, various grout types, and the grout compressive strength. The results showed that RMBEs built with rectangular sections exhibited enhanced strain ductility and post-peak behaviour than square RMBEs. Besides, using low grout compressive strength significantly reduced the strain ductility and yielded sharp strength degradation of the RMBEs.
The RMBEs′ experimental results revealed that the monotonic stress-strain curves form envelope curves to their cyclically tested counterparts. The proposed monotonic and cyclic stress-strain models showed good-to-excellent agreement with the experimental results, predicting the envelope and cyclic stress-strain curves′ major characteristics.
The numerical study’s results showed that the seismic design of RMSW+BEs can be optimized through careful choice of their design parameters. Enhancing the RMSW+BEs lateral yield and ultimate capacities and the lateral effective stiffness can be achieved by increasing the vertical reinforcement ratio of the RMBEs and the masonry compressive strength. Contrarily, reducing the masonry strain at peak stress and/or the masonry modulus of elasticity greatly hinders the walls′ displacement ductility.


identifier: Labana, Mohamed  (2021) Performance Optimization of Cloud Radio Access Networks.  Masters thesis, Concordia University.

abstract:
The exponential growth of cellular data traffic over the years imposes a hard challenge on the next cellular generations. The cloud radio access network (CRAN) is an emerging cellular architecture that is expected to face that challenge effectively. The main difference between the CRAN architecture and the conventional cellular architecture is that the baseband units (BBUs) are aggregated at a centralized baseband unit pool, hence, enabling statistical multiplexing gains. However, to acquire the several advantages offered by the CRAN architecture, efficient optimization algorithms and transmission techniques should be implemented to enhance the network performance. Hence, in this thesis, we consider jointly optimizing user association, resource allocation and power allocation in a two tier heterogeneous cloud radio access network (H-CRAN). Our objective is to utilize all the network resources in the most efficient way to maximize the network average throughput, while keeping some constraints such as the quality of service (QoS), interference protection to the devices associated with the Macro remote radio head (MRRH), and fronthaul capacity. In our system, we propose using coordinated multi-point (CoMP) transmissions to utilize any excess resources to maximize the network performance, in contrast to the literature, in which CoMP is usually used only to support edge users. We divide our joint problem into three sub-problems: user association, radio resource allocation, and power allocation. We propose matching game based low complexity algorithms to tackle the first two sub-problems. For the power allocation sub-problem, we propose a novel technique to convexify the non-convex original problem to obtain the optimal solution. Given the conducted simulations, our proposed algorithms proved to enhance the network average weighted sum rate significantly, compared to the state of the art algorithms in the literature.
The high computational complexity of the optimization techniques currently proposed in the literature prevents from totally reaping the benefits of the CRAN architecture. Learning based techniques are expected to replace the conventional optimization techniques due to their high performance and very low online computational complexity. In this thesis, we propose tackling the power allocation in CRAN via an unsupervised deep learning based approach. Different from the previous works, user association is considered in our optimization problem to reflect a real cellular scenario. Additionally, we propose a novel scheme that can enhance the deep learning based power allocation approaches, significantly. We provide intensive analysis to discuss the trade-offs faced when employing our deep learning based approach for power allocation. Simulation results prove that the proposed technique can obtain a very close to optimal performance with negligible computational complexity.


identifier: Stahl, Darian Goldin ORCID: https://orcid.org/0000-0002-8853-9902 <https://orcid.org/0000-0002-8853-9902>  (2021) Book as Body: The Meaning-Making of Artists' Books in the Health Humanities.  PhD thesis, Concordia University.

format: text video image image image image image image image image image image image

abstract: This research-creation dissertation investigates how artists’ books’ text, images, form, materiality, and other sensory engagements merge to communicate lived experiences of illness and disability. I ask how the meanings of these abstracted book-bodies adapt and change when they are re-interpreted by readers, and how this can be an effective strategy for forming relational understandings of what it is like to live with illness. Within the framework of a phenomenological practice, I show the generative potential for empathy and intercorporeal exchange that often occurs when engaging with another’s artist’s book. Next, I describe past practices of artists who have deployed artists’ books in negotiating the biomedicalization of their illness experience. I then reflect upon my own contribution to the intersection of artists’ books and healthcare, Field Notes: How to Be With. Finally, I analyze the outcomes of artist’s book workshops I developed and conducted with multiple communities, including biomedical personnel. These distinct, but inter-related research-creation practices indicate how patient communities can devise tacit and multi-sensory expressions of embodied phenomena that may otherwise be difficult to communicate through verbal means alone. From a health humanities perspective, the pedagogical potential of reading and making artists’ books may assist in resisting systemic pressures for clinical efficiency and unseat biases towards illness and disability. This research-creation dissertation thus serves as a philosophical, pedagogical, and pragmatic example of how to engage with artists’ books in health contexts. It examines how the formation of archival, hand-made book objects constitutes a legacy of lived experience that may be called upon, again and again, to share and understand life, death, illness, health, unease, and wellbeing.


identifier: Goldman, Dan Misha  (2021) Exploring The Role of Mindfulness in Music Therapy: A Qualitative Interview Study.  Masters thesis, Concordia University.

abstract: Mindfulness as a concept and a practice has become ubiquitous amongst health professionals. However, only a small number of studies have investigated the use of  mindfulness approaches within music therapy. The purpose of this study was to understand how mindfulness-meditation may influence a music therapist’s clinical practice. Three highly experienced music therapists, who each maintain a daily mindfulness-meditation practice, were interviewed. The semi-structured interviews were recorded, transcribed and analyzed according to Neuman’s (2006) qualitative data analysis techniques. Emergent themes were set within five overarching categories including: defining mindfulness, self-care, therapeutic presence, the use of mindfulness-oriented approaches within sessions, and recommendations to other music therapists. The results suggested that mindfulness may factor into clinical practice in both implicit and explicit ways, and that a mindful awareness may enhance therapeutic efficacy within a music therapy context. Implications for clinical practice and educational settings are discussed. Limitations of the study are also highlighted along with recommendations for future research.


identifier: Torabi, Sadegh ORCID: https://orcid.org/0000-0003-2811-3536 <https://orcid.org/0000-0003-2811-3536>  (2021) Data-Driven Approaches for Detecting Malware-Infected IoT Devices and Characterizing Their Unsolicited Behaviors by Leveraging Passive Internet Measurements.  PhD thesis, Concordia University.

abstract:
Despite the benefits of Internet of Things (IoT) devices, the insecurity of IoT and their deployment nature have turned them into attractive targets for adversaries, which contributed to the rise of IoT-tailored malware as a major threat to the Internet ecosystem. In this thesis, we address the threats associated with the emerging IoT malware, which utilize exploited devices to perform large-scale cyber attacks (e.g., DDoS). To mitigate such threat, there is a need to possess an Internet perspective of the deployed IoT devices while building a better understanding about the behavioral characteristic of malware-infected devices, which is challenging due to the lack of empirical data and knowledge about the deployed IoT devices and their behavioral characteristics.

To address these challenges, in this thesis, we leverage passive Internet measurements and IoT device information to detect exploited IoT devices and investigate their generated traffic at the network telescope (darknet). We aim at proposing data-driven approaches for effective and near real-time IoT threat detection and characterization. Additionally, we leverage a specialized IoT Honeypot to analyze a large corpus of real IoT malware binary executable. We aim at building a better understanding about the current state of IoT malware while addressing the problems of IoT malware classification and family attribution. To this end, we perform the following to achieve our objectives:

First, we address the lack of empirical data and knowledge about IoT devices and their activities. To this end, we leverage an online IoT search engine (e.g., Shodan.io) to obtain publicly available device information in the realms of consumer and cyber-physical system (CPS), while utilizing passive network measurements collected at a large-scale network telescope (CAIDA), to infer compromised devices and their unsolicited activities. Indeed, we were among the first to report experimental results on detecting compromised IoT devices and their behavioral characteristics in the wild, while demonstrating their active involvement in large-scale malware-generated malicious activities such as Internet scanning. Additionally, we leverage the IoT-generated backscatter traffic towards the network telescope to shed light on IoT devices that were victims of intensive Denial of Service (DoS) attacks.

Second, given the highly orchestrated nature of IoT-driven cyber-attacks, we focus on the analysis of IoT-generated scanning activities to detect and characterize scanning campaigns generated by IoT botnets. To this end, we aggregate IoT-generated traffic and performing association rules mining to infer campaigns through common scanning objectives represented by targeted destination ports. Further, we leverage behavioural characteristics and aggregated flow features to correlate IoT devices using DBSCAN clustering algorithm. Indeed, our findings shed light on compromised IoT devices, which tend to operate within well coordinated IoT botnets.

Third, considering the huge number of IoT devices and the magnitude of their malicious scanning traffic, we focus on addressing the operational challenges to automate large-scale campaign detection and analysis while generating threat intelligence in a timely manner.
To this end, we leverage big data analytic frameworks such as Apache Spark to develop a scalable system for automated detection of infected IoT devices and characterization of their scanning activities using our proposed approach. Our evaluation results with over 4TB of IoT traffic demonstrated the effectiveness of the system to infer scanning campaigns generated by IoT botnets. Moreover, we demonstrate the feasibility of the implemented system/framework as a platform for implementing further supporting applications, which leverage passive Internet measurement for characterizing IoT traffic and generating IoT-related threat intelligence.

Fourth, we take first steps towards mitigating threats associated with the rise of IoT malware by creating a better understanding about the characteristics and inter-relations of IoT malware. To this end, we analyze about 70,000 IoT malware binaries obtained by a specialized IoT honeypot in the past two years. We investigate the distribution of IoT malware across known families, while exploring their detection timeline and persistent. Moreover, while we shed light on the effectiveness of IoT honeypots in detecting new/unknown malware samples, we utilize static and dynamic malware analysis techniques to uncover adversarial infrastructure and investigate functional similarities. Indeed, our findings enable unknown malware labeling/attribution while identifying new IoT malware variants. Additionally, we collect malware-generated scanning traffic (whenever available) to explore behavioral characteristics and associated threats/vulnerabilities.

We conclude this thesis by discussing research gaps that pave the way for future work.


identifier: Crespo, A. M. F. ORCID: https://orcid.org/0000-0003-3960-0858 <https://orcid.org/0000-0003-3960-0858>  (2021) Computational Learning Framework for Carbon Emissions Predictions Incorporating a RReliefF Driven Features Selection and an Iterative Neural Network Architecture Improvement.  PhD thesis, Concordia University.

abstract:
Environmental protection is being progressively considered as paramount condition for the planet's continued habitability. After the Kyoto Protocol signature in 1997, governments, industry stakeholders and academia began to work on the development of effective and efficient environmentally driven policies and economic mechanisms, and the proper design of such parameters is critically dependent on carbon emissions projections. In such scenario, inaccurate carbon emissions predictions may be one of the root factors leading to the overall ineffectiveness of the European Union environmental regulatory framework.
Therefore, the present thesis introduces a novel computational learning framework for carbon emissions prediction incorporating a RReliefF driven features selection and an iterative neural network architecture improvement. Our learning framework algorithmic architecture iteratively chains the features selection process and the backpropagation artificial neural network (NN/BP) architecture design based on the data assessment accomplished by the RReliefF algorithm. Thus a better features set - NN/BP architecture combination is obtained for each specific prediction target.
The implemented framework was trained and validated with real world data obtained from the European Union (Eurostats), the International Energy Agency, the Organization for Economic Co-operation and Development, and the World Bank. The validation dataset comprised 26 potential predictors covering the period 1990 - 2014. Additionally, a case study was conducted with a new dataset comprising data obtained from the World Resources Institute's Climate Data Explorer (CAIT), and the World Bank database. The case study dataset comprises 24 potential predictors covering the period 1970 - 2014.
The learning framework also features an Explainable Artificial Intelligence (XAI) module that provides explanations of the predictions in terms of global features impact and local features weights. The global model explanations are computed by means of partial dependence functions, while local model explanations are computed by means of the interpretable model-agnostic explanations (LIME) algorithm.
The framework evaluation against current mainstream machine learning models, and its benchmarking comparing to recent published researches on carbon emissions prediction indicates that our research contribution is relevant and capable of supporting the improvement of environmental policies. The learning framework outcomes are also expected to provide some ground for future researches targeting carbon emissions causality analysis, as well as potential improvements on both ANNs and XAI techniques.


identifier: Abdelrahman, Diaaeldin  (2021) Modeling and Design of High-Speed CMOS Receivers for Short-Reach Photonic Links.  PhD thesis, Concordia University.

abstract:
This dissertation presents several research outcomes towards designing high-speed CMOS optical receivers for energy-efficient short-reach optical links. First, it provides a wide survey of recently published equalizer-based receivers and presents a novel methodology to accurately calculate their noise. The proposed methodology is then used to find the receiver that achieves the best sensitivity.
Second, the trade-off between sensitivity and power dissipation of the receiver is optimized to reduce the energy consumption per bit of the overall link. Design trade-offs for the receiver, transmitter, and the overall link are presented, and comparisons are made to study how much receiver sensitivity can be sacrificed to save its power dissipation before this power reduction is outpaced by the transmitter’s increase in power. Unlike conventional wisdom, our results show that energy-efficient links require low-power receivers with input capacitance much smaller than that required for noise-optimum performance.
Third, the thesis presents a novel equalization technique for optical receivers. A linear equalizer (LE) is realized by adding a pole in the feedback paths of an active feedback-based wideband amplifier. By embedding the peaking in the main amplifier (MA), the front-end meets the sensitivity and gain of conventional LE-based receivers with better energy efficiency by eliminating the standalone equalizer stage(s). Electrical measurements are presented to demonstrate the capability of the proposed technique in restoring the bandwidth and improving the performance over the conventional design.


identifier: Chakrabarti, Trina  (2021) Therapeutic Songwriting in Adolescent Inpatient Mental Health Care: A Program Intervention Research to Address Psychosocial Strengths and Needs.  Masters thesis, Concordia University.

abstract:
This research study explores the development of a therapeutic songwriting-based program intervention for adolescents in inpatient mental health care contexts.The related literature looked at how music therapy songwriting methods are used to address the psychosocial strengths and needs of youth in inpatient mental health care, particularly, needs of emotional processing, identity formation, and being connected, as reported by McFerran et al., (2019). The intervention research design followed the first one-and-a-half steps of the Fraser and Galinsky (2010) model. These steps included an analysis of risk and protective factors through deductive coding of relevant literature, which led to a program theory. The program intervention protocol involves a referral, an intake, and a three-phase model that is ideally realized within three 45- to 60-minute individual sessions. The phases of the model are
(1) assessment, (2) free writing and exploration, and (3) structured implementation leading to the completion of a song composition. Music therapists using this program intervention should have
knowledge of adolescents’ unique mental health care needs, be proficient in a variety of music genres, and have a flexible therapeutic approach. Future research could aim to develop the
intervention further and to evaluate the effects of its implementation in an inpatient adolescent psychiatric unit.


identifier: Mason, Joel  (2021) Plenum Life: Formality in the Movement of Free Ecology.  PhD thesis, Concordia University.

abstract:
This work centres on a specific functional moment in the creation of collective self-defense: a novel reconceptualization of the endurance (and the negotiations around endurance) of forms that protect the conditions for emergence. Thus this thesis seeks to forward and invent theories and techniques of technological-financial-governmental activation that self-dispossess the ‘source code’ in these  fields so activated, informed by the black radical tradition, process philosophy, and interaction-as-computation category theory.

It seeks this forwarding by articulating a new role for formality in the world through the perversion of the discourse of the philosophy of engineering (one already happening, partially, within itself). This thesis is interested in the hypothesis that (1) there is nothing proprietary in informality’s production of the social economic conditions associated with it, (2) formality may then play a role in such productions, augmenting key functional aspects, such as the option for endurance, and adding to the field its own expressive inventions, not only without hampering or dislodging what Denise Ferreira da Silva calls the poethical, but perhaps revealing how it participates in the poethical, and (3) that an articulation of such a role will reveal new frameworks for organizational design tout court, frames able to ripple through practices and disciplines previously thought to be discrete and siloed.


identifier: Trottier Cournoyer, Maryse  (2021) Music-Centered Music Therapy with Youth in Mental Health Care Contexts: A Philosophical Inquiry.  Masters thesis, Concordia University.

abstract: The purpose of this research was to understand how the needs of youth in mental health care contexts might be met through music-centered music therapy. This philosophical inquiry used Aigen’s (2005a) five dimensions of music-centered music therapy; the creative, expressive, aesthetic, communal, and transpersonal dimensions, to reason why this approach has clinical relevance with youth in mental health care contexts. Literature relating to music-centered music therapy, the needs of youth in mental health care contexts, and the use of music therapy with this population were explored in order to formulate a basis for the inquiry. The needs of youth in mental health care contexts were developed according to research on the needs of youth in general and the needs specific to youth in mental health care contexts. Needs relating to expressing emotion, understanding and formation of self, connectedness and belonging, feeling empowered, and coping with symptoms of mental illness were identified. Using the five dimensions of music centered music therapy as a lens to explore their interaction with the needs of youth in mental health care contexts, intersections and new insights were conceptualized. Lastly, the research findings, clinical implications, research implications and limitations are discussed. This research may be used as a resource for the use of music-centered music therapy with youth in mental health care contexts, and the emergent themes may serve as a starting point for additional research.


identifier: Bray, Miranda  (2021) Music Therapy in the Neonatal Intensive Care Unit: Prevalence and Presentation of Parental Empowerment: An Integrative Literature Review.  Masters thesis, Concordia University.

abstract: This integrative literature review investigated, synthesized, and analysed research relating to caregiver empowerment in Neonatal Intensive Care Unit (NICU) music interventions. As many as 70% of mothers and 30% of fathers face mental health disruptions in the NICU. Because of this, there is an identified need to address parental health and wellbeing in the NICU. Literature on empowering parents in the NICU and its potential positive implications on their wellbeing have been examined in other disciplines but have yet to be explored in the context of music therapy. In this study, 28 articles including 27 peer-reviewed journals and one book chapter were examined and coded based on intervention and themes of empowerment. The review explored four facets of empowerment including self-regulation, sensitivity, engagement, and nurturing strengths and potentials. It uncovered that: (a) empowerment can come from a wide variety of music therapy interventions, (b) the most commonly addressed theme of empowerment was self-regulation, followed by nurturing of strengths and potentials, engagement, and sensitivity, and (c) when an article used the word empowerment it always contained at minimum two facets of empowerment. Of the 28 qualifying articles included in this study, 3 (10.7%) included no empowerment themes, 8 (28.6%) included only one theme of empowerment, 8 (28.6%) included two themes of empowerment, 5 (17.9%) included 3 themes of empowerment, and 4 (14.3%) included all four themes of empowerment. These results indicate that further research is needed to investigate the impact, application, and role of empowerment in NICU music therapy with caregivers. Future research and recommendations are presented.


identifier: Mouradian, Lala  (2021) Monuments and Memory: The Remediation and the Visual Appropriations of the Mother Armenia Statue on Instagram During the 2020 Nagorno-Karabakh War.  Masters thesis, Concordia University.

abstract: This thesis analyzes the remediation and the visual appropriations of the Mother Armenia statue on Instagram during the 2020 Nagorno-Karabakh war. The Mother Armenia statue was erected in 1967 in Armenia’s capital city of Yerevan as a female personification of Armenia. Its meaning and symbolism have been reworked during different collective crises for the Armenian nation. During the 2020 Nagorno-Karabakh war, the statue was a significant object of appropriation in the production and sharing of images on Instagram both by Armenians living in Armenia and the Armenian diaspora. This thesis examines the Instagram images in relation to historical and contemporary understandings of the concept of Armenian motherhood, the history of the construction and symbolism of the Mother Armenia statue, the intersection of monuments and memory studies, and visual cultural studies.


identifier: Zhang, Yi  (2021) Efficient Asynchronous GCN Training on a GPU Cluster.  Masters thesis, Concordia University.

abstract: A common assumption in traditional synchronous parallel training of Graph Convolutional Networks (GCNs) using multiple GPUs is that load is perfectly balanced among all GPUs. However, this assumption does not hold in a real-world scenario where there can be imbalances in workloads among GPUs for various reasons. In a synchronous parallel implementation, a straggler in the system can limit the overall speed-up of parallel training. To address these issues, this research investigates approaches for asynchronous decentralized parallel training for GCNs. The techniques investigated are based on graph clustering and gossiping. The research specifically adapts the approach of Cluster-GCN, which uses graph partitioning for SGD-based training, and combines with a novel gossip algorithm specifically designed for a GPU cluster to periodically exchange gradients among randomly chosen partners. In addition, it incorporates a work-pool mechanism for load balancing among GPUs. The gossip algorithm is proven to be deadlock free. The implementation is done on a GPU cluster with 8 Tesla V100 GPUs per compute node, and PyTorch and DGL as the software platforms. Experiments are conducted for different benchmark datasets. The results demonstrate superior performance, at the compromise of minor accuracy loss in some runs, as compared to traditional synchronous training which uses all-reduce to synchronously accumulate parallel training results.


identifier: Shewchuk, Glenn ORCID: https://orcid.org/0000-0002-9216-6969 <https://orcid.org/0000-0002-9216-6969>  (2021) Medical Assistance in Dying: Exploring an Evangelical Approach to the Laws Surrounding MAID in Canada and an Application of Scripture to MAID and Suicide.  Masters thesis, Concordia University.

abstract: Medical Assistance in Dying is presently a reality in Canada. There are numerous changes which have gradually taken place in Canadian society and in the Canadian legal context to bring about the legalization of MAID. There is extensive literature available on the topic, but little scholarly literature from an Evangelical Christian perspective. The Truchon court decision and Bill C-7 have raised concerns that access to euthanasia could continue to be extended and promoted until it endangers vulnerable Canadians, (which is called “the slippery slope”). Ableism, the emphasis that able bodies are the norm, has also been an influence on the legalization of MAID and therefore an area of deep concern for the disabled. The possible removal of restrictions for persons with mental health issues poses serious ethical questions. Evangelicals have a strong view of the authority of the Bible. The Scriptures are examined in application to MAID.


identifier: Mobasheramini, Fatane  (2021) Quantization of Calogero-Painleve system and Multi-particle quantum Painleve equations II-VI.  PhD thesis, Concordia University.

abstract:
In this dissertation, we implement canonical quantization within the framework of the so-called Calogero-Painleve correspondence for isomonodromic systems. The classical systems possess a group of symmetries and in the quantum version, we implement the (quantum) Hamiltonian reduction using the Harish-Chandra homomorphism. This allows reducing the matrix operators to Weyl-invariant operators on the space of eigenvalues. We then consider the scalar quantum Painleve equations as Hamiltonian systems and generalize them to multi-particle systems; this allows us to formulate the multi-particle quantum time-dependent Hamiltonians for the Schrödinger equation.

We then generalize certain integral representations of solutions of quantum Painleve equations to the multi-particle case. These integral representations are in the form of special beta ensembles of eigenvalues and can be constructed for all the Painleve equations except the first one. They play the role, in the quantum world, of rational solutions in the classical world.

These special solutions exist only for particular values of the quantum Hamiltonian reduction parameter (or coupling constant). We elucidate the special values of the corresponding parameters appearing in the quantized Calogero-Painleve equations II-VI.


identifier: Safaie, Tina  (2021) BYPASS: RECONSIDERING THE USABILITY OF PASSWORD MANAGERS.  Masters thesis, Concordia University.

abstract:
Since passwords are an unavoidable mechanism for authenticating to online services, experts often recommend using a password manager for better password security. However,  adoption of password managers is low due to poor usability, the difficulty of migrating accounts to a manager, and users' sense that a manager will not add value. In this work, we present ByPass, a novel password manager that is placed between the user and the website for secure and direct communication between the manager and websites. This direct communication allows ByPass to minimize the users' actions needed to complete various password management tasks, including account registration, logins, and password changes. ByPass is designed to minimize errors and improve usability. Our goal is to create a space where security could be the users' primary task, and allow them to focus cleanly and consistently on account management tasks. The constancy of the ByPass interface is intended to allow users a greater sense of control over their passwords and accounts. By using the API to move account interactions into this space, we hope to create an interface where users knew where to address security concerns, and access the controls to address those concerns. Current password managers hint at this functionality (and include innovative tools, such as security audits) but their placement outside the authentication interaction hampers the functionality they are able to support.

We conducted a usability evaluation of ByPass and found that this approach shows promising usability, and can help users to better manage their accounts in a secure manner.

We also conducted a security analysis of ByPass and showed the security improvements that can be achieved with the support of APIs for password managers. Our study shows that many known security vulnerabilities can be eradicated from the foundation of password managers, and significant usability can be gained with the inclusion of APIs support for password managers.


identifier: Cote, Ann Marie  (2021) How can we Bridge the Gap: Health Literacy among Older Adults Diagnosed with Diabetes.  Masters thesis, Concordia University.

abstract: A review of the literature confirms that health literacy impacts society tremendously. This research project responds to the question: How can the gap between health literacy efforts and educating older diabetic adults be bridged? The aging of the population, as well as a greater absolute increase in the prevalence of diabetes among elderly people is expected to become an epidemic. While online health information has lessened the gap, as it is free and often simplified, the emphasis is on self-management and self-care, leaving some individuals still without easy access to health care guidance. Currently there is a global push from governing agencies to improve health literacy. Overall, patients with low health literacy need to understand the implications of diabetes and how they can better cope with it. This exploratory qualitative research study explores the literature, searching for gaps in what is known, and conducts narrative interviews to understand how to bridge the gap between health literacy efforts and older diabetic adults. It concludes that improving health literacy within this population requires more transmission of health information, promoting health education that will improve individuals’ confidence  and ability to self-manage their care.


identifier: Hart, Eleanor  (2021) Music Therapists’ Experiences and Perspectives in Working with LGBTQ+ Youth in Canada.  Masters thesis, Concordia University.

abstract: LGBTQ+ youth are a diverse group of individuals with a variety of experiences, strengths, and resources. However, this group is at greater risk of mental and physical health challenges due to the systemic oppression and marginalization they face. Research has begun to explore how music therapy can support LGBTQ+ youth in navigating these challenges, but there is currently a lack of literature on this topic in Canada. The purpose of this qualitative interview study was to understand the experiences and perspectives of certified music therapists (MTAs) in their work with LGBTQ+ youth in Canada. Semi-structured qualitative feminist interviews were conducted with three participants over Zoom. Interviews were analyzed using qualitative thematic analysis with a critical lens. The three overarching themes that emerged in the results were (a) client priorities; (b) music therapist competence, commitments, and reflexivity; and (c) representation, visibility, and shared experiences. Implications are discussed for Canadian music therapy practice, training and education, and research, and limitations of the study are presented. This study aims to expand knowledge of how music therapists in Canada can best support LGBTQ+ youth clients, contribute to the development of more music therapy programs for these clients, and initiate more research in this area.


identifier: Doyle, Audrey-Anne  (2021) Domestic Workers’ Strategies of Resistance to Chronic Workplace Violence in Medellín, Colombia.  Masters thesis, Concordia University.

abstract: In Colombia, 94% of domestic workers are women and they make up 7% of the female workforce (DANE 2020). Approximately 80% are Afro-Descendant or Indigenous and 25% of those working in Cali, Medellin and Bogota have been displaced by the ongoing armed conflict. Domestic workers often work long hours in exchange for low wages; do not have access to social security or social benefits; are victims of physical, verbal and/or sexual abuse; and are not perceived by society as valuable members of the workforce (De Cicco 2014; Donaldson and Osorio 2016; Moreno-Salamanca 2017). This thesis examines the centuries of social, economic, and institutional persecution of “othered” races and classes that feed chronic violence against domestic workers in contemporary Colombian society. This structural violence also determines what strategies are used to resist workplace violence and the extent to which these strategies are effective. In addition, this thesis explores the impact of unionization on everyday resistance strategies. Findings from ethnographic research and semi-structured interviews in Medellin, Colombia indicate that resistance under the form of exit, confrontation and negotiation have allowed domestic workers to guarantee their survival (physical and mental preservation), promote contextual adjustments (attenuate oppression and improve access to resources) and cause positive transformations in the structural sources of abuse (Mayer 2021).


identifier: El Ramli, Shadi Nezar  (2021) Three Essays on Monetary Policy and Macroeconomics Stability.  PhD thesis, Concordia University.

abstract: The three chapters of the thesis are centered around monetary policy and macroeconomic stability. In the first chapter, a DSGE model is simulated and estimated to evaluate the macroeconomic effect of credit-demand shocks versus credit- supply shocks. The model features two financial shocks originating on the credit-demand side and one shock originating on the credit-supply side. Model simulations show that credit-demand shocks could generate significant macroeconomic fluctuations, up to three times the impact of credit-supply shocks. Bayesian estimation of the parameters of the shocks and variance decomposition show that credit-demand shocks caused 17\% of the fluctuation in output. The second paper investigates the role of monetary policy in the rise of household debt in the periods leading to the Great Recession. A Factor-Augmented Vector Autoregression (FAVAR) model is estimated in multiple periods. Tests of stability of the estimated coefficients suggest the existence of a structural break, which is interpreted as a change in the transmission mechanism in periods of low versus high household debt. Monetary policy shocks during both periods are identified by Cholesky decomposition. The paper shows that during the period of higher household debt, the volatility of monetary policy shocks was lower and the impulse responses of output and household debt to monetary policy shocks were stronger. Estimates of monetary policy reaction functions in the two periods suggest the stronger response of output and household debt in the second period might have been due to a combination of a stronger transmission mechanism and a weaker monetary policy reaction. The final chapter of the thesis investigates whether monetary policy surprises affect home equity excess returns, and whether the effect transmits through expected future interest rates, expected future dividends, or expected future excess returns. Home equity excess returns are decomposed into three components using a forecasting VAR model. The three decomposed components are then used to estimate a VAR model where monetary policy shocks are identified by Cholesky decomposition. Analysis of the generated impulse responses shows that, unlike its effect on stock equity returns, the effect of monetary policy surprises on home returns transmits through interest rate and future dividends channels more than through the risk premium channel.


identifier: Syutkin, Anatoly  (2021) Hardware Implementation of Spiking Neural Networks.  Masters thesis, Concordia University.

abstract:
The fields of Machine Learning and Artificial Intelligence have made great strides in the last decade due to the increasing computational power of Graphics Processing Units (GPUs). Neural networks make up for a very large portion of this research area, and come in great variety (e.g. feedforward, convolutional, etc.). Although they are inspired by the human brain, they have no biological plausibility aside from the high interconnectivity of nodes. Spiking Neural Networks (SNNs) are a step in the direction of greater biological plausibility with the use of inherently dynamic neurons.
As implied by the name, SNNs are composed of neurons that generate Boolean spikes when their accumulated input exceeds a threshold value. Thus, information is encoded in the timing of spiking events. Although they are computationally expensive to simulate with general-purpose computers, their dynamic behavior lends itself well to direct hardware implementations with very high parallelism and low power consumption.
This thesis proposes a scalable architecture for a hardware system that can be used to study the behavior of SNNs, as well as the trade-offs that result from the various design parameters. Using classic benchmark problems (i.e. MNIST classification and cart-pole stabilization), it was observed that SNNs are very robust against variations in neural parameters, but degrade quickly with mismatch in synaptic weights. An MNIST classification accuracy of 96.28% drops by < 2% for severe neural variations, but > 5% for small synaptic mismatches. Additionally, the performance is re-evaluated for several weight quantizations. Finally, the effects of router delays are observed.


identifier: Mirarabshahi, Shirinalsadat  (2021) Modeling and Analysis of a Hybrid Production System in Electronics Industries Using System Dynamics.  Masters thesis, Concordia University.

abstract: Sustainable production has become a significant concern over recent years due to environmental considerations and material scarcity. Consequently, the closed-loop supply chain concept has been developed to reduce waste, decrease environmental issues, and maximize material utilization. Manufacturers attempt to add different recovery strategies to the traditional production system and close the forward production flow to create a closed-loop supply chain. In this research, a hybrid production system applied in an electronics manufacturing company is studied. Two recovery strategies, remanufacturing and recycling, are considered to make a hybrid production system. Although remanufacturing and recycling are recognized in the literature as promising recovery strategies, the profitability of using them for the manufacturers is still controversial. This research presents a system dynamics model addressing the analysis of a hybrid production system in an electronics manufacturing company. The objective of the system dynamics simulation is to evaluate impacts resulting from using remanufacturing and recycling on two critical parameters, including total profit and cost per unit. For this purpose, the model is run using parameters and information related to a laptop manufacturing company to compare production scenarios, evaluate the system performance in terms of economic benefits, and provide insights for policymakers for designing policies that align with the manufacturers' benefits.


identifier: Orfanos, Emmanuel  (2021) Caloric Restriction Causes a Distinct Remodeling of the Lipidome in Quiescent Cells of Budding Yeast.  Masters thesis, Concordia University.

abstract:
After budding yeast cells cultured in a nutrient-rich liquid medium with glucose ferment glucose to ethanol and then consume it as a carbon source, they enter the stationary phase of culturing and the process of their chronological aging begins. At that point, yeast cells in the culture arrest their cell cycle and enter a state of quiescence, also known as the G0 state. Shortly following such cell cycle arrest, the yeast culture begins to accumulate quiescent and non-quiescent cells. The Titorenko laboratory has recently used gradient centrifugation to purify the high- and low-density sub-populations quiescent and non-quiescent cells. They demonstrated that caloric
restriction, a robust aging-delaying (geroprotective) dietary intervention, decreases the concentrations of the neutral storage lipids triacylglycerols and increases the concentration of the mitochondrial membrane lipid cardiolipin in quiescent and non-quiescent cells. The studies described in my Thesis had the following two objectives. First, I sought to investigate how caloric restriction influences the concentrations of all lipid classes (not only triacylglycerols and cardiolipin concentrations) within the high- and low-density sub-populations of quiescent and nonquiescent yeast cells on different stages of the chronological aging process. My second objective was to compare the effects of caloric restriction, the tor1Δ mutation (a genetic geroprotective intervention) and lithocholic acid (a pharmacological geroprotective intervention) on the lipidomes
of the high- and low-density sub-populations of quiescent and non-quiescent yeast cells on different stages of chronological aging. To attain these objectives, I used liquid chromatography
coupled with tandem mass spectrometry quantitative lipidomics to assess the aging-associated changes in high- and low-density cells’ lipidomes. I provided the first evidence that caloric
restriction statistically significantly alters the concentrations of 18 different lipid classes through most of the chronological lifespan of high- and low-density cells. Caloric restriction decreased triacylglycerol concentration, increased free fatty acid concentration, raised ceramide concentration, and elevated phospholipid concentrations in high- and low-density cells through most of the chronological lifespan. My data also provided the first evidence that caloric restriction creates lipidomic patterns of chronologically aging high- and low-density cells that differ from the lipidomic patterns of these cells established by the tor1Δ mutation and lithocholic acid.


identifier: Atallah, Ayman ORCID: https://orcid.org/0000-0003-1747-0749 <https://orcid.org/0000-0003-1747-0749>  (2021) Design of Time-Sensitive Networks For Safety-Critical Cyber-Physical Systems.  PhD thesis, Concordia University.

abstract:
A new era of Cyber-Physical Systems (CPSs) is emerging due to the vast growth in computation and communication technologies. A fault-tolerant and timely communication is the backbone of any CPS to interconnect the distributed controllers to the physical processes. Such reliability and timing requirements become more stringent in safety-critical applications, such as avionics and automotive. Future networks have to meet increasing bandwidth and coverage demands without compromising their reliability and timing. Ethernet technology is efficient in providing a low-cost scalable networking solution. However, the non-deterministic queuing delay and the packet collisions deny low latency communication in Ethernet. In this context, IEEE 802.1 Time Sensitive Network (TSN) standard has been introduced as an extension of the Ethernet technology to realize switched network architecture with real-time capabilities. TSN offers Time-Triggered (TT) traffic deterministic communication. Bounded Worst-Case end-to-end Delay (WCD) delivery is yielded by Audio Video Bridging (AVB) traffic. In this thesis, we are interested in the TSN design and verification.

TSN design and verification are challenging tasks, especially for realistic safety-critical applications. The increasing complexity of CPSs widens the gap between the underlying networks' scale and the design techniques' capabilities. The existing TSN's scheduling techniques, which are limited to small and medium networks, are good examples of such a gap. On the other hand, the TSN has to handle dynamic traffic in some applications, e.g., Fog computing applications. Other challenges are related to satisfying the fault-tolerance constraints of mixed-criticality traffic in resource-efficient manners. Furthermore, in space and avionics applications, the harsh radiation environment implies verifying the TSN's availability under Single Event Upset (SEU)-induced failures. In other words, TSN design has to manage a large variety of constraints regarding the cost, redundancy, and delivery latency where no single design approach fits all applications. Therefore, TSN's efficient employment demands a flexible design framework that offers several design approaches to meet the broad range of timing, reliability, and cost constraints.

This thesis aims to develop a TSN design framework that enables TSN deployment in a broad spectrum of CPSs. The framework introduces a set of methods to address the reliability, timing, and scalability aspects. Topology synthesis, traffic planning, and early-stage modeling and analysis are considered in this framework. The proposed methods work together to meet a large variety of constraints in CPSs. This thesis proposes a scalable heuristic-based method for topology synthesis and ILP formulations for reliability-aware AVB traffic routing to address the fault-tolerance transmission. A novel method for scalable scheduling of TT traffic to attain real-time transmission. To optimize the TSN for dynamic traffic, we propose a new priority assignment technique based on reinforcement learning. Regarding the TSN verification in harsh radiation environments, we introduce formal models to investigate the impact of the SEU-induced switches failures on the TSN availability. The proposed analysis adopts the model checking and statistical model checking techniques to discover and characterize the vulnerable design candidates.


identifier: Sciascia, Christina  (2021) Postpartum Depression and Parent-Infant Attachment: A Music Therapy Program Intervention Research.  Masters thesis, Concordia University.

abstract:
ABSTRACT

Postpartum Depression and Parent-Infant Attachment: A Music Therapy Program Intervention Research

Christina Sciascia
This study proposes a music therapy intervention program designed to promote the early attachment of parent-infant dyads that are affected by postpartum depression (PPD).  Step one and part of step two of Fraser and Galinsky’s (2010) approach to intervention research design was used to develop the program framework. The student-researcher reviewed 13 published Music Therapy articles and 12 published articles from related literature regarding early attachment. Other seminal works were included for context, definitions and theoretical underpinnings. The student-researcher used a directed content analysis approach to extract and analyze data necessary for developing and implementing the program. Results are presented through tables and a proposed intervention program.  The findings show that the symptoms of PPD could impair parents’ well-being and relational abilities which likely compromises parent-infant attachment and has negative effects on infant development in the short and long term. This music therapy program is designed to act upon identified variables in order to prevent and/or mitigate the potentially damaging effects of PPD on attachment and infant development. The main actions used to achieve these goals are group music therapy and coaching of wellness techniques and parenting skills. Future research and recommendations are presented.


identifier: Zhang, Zhenfei  (2021) Localizing Object by Using only Image-level Labels.  Masters thesis, Concordia University.

abstract: Weakly Supervised Object Localization (WSOL) task attracts more and more attention in recent years, which aims to locate the object by using incomplete labels. Considering the cost of annotation, especially ground-truth bounding box label and training speed of detection task, it is very necessary to improve the performance of WSOL that only requires image-level labels. Most current methods tend to utilize Class Activation Map (CAM) that can only highlight the most discriminative parts rather than the entire target. The common method to address this kind of limitation is to hide the most obvious regions and let the model learn other parts of the target. The main work of this thesis is to eliminate the limitations of current WSOL work and improve the performance of localization. In chapter 3, we design an attention-based selection strategy to dynamically hide the feature maps. In chapter 4, a new hiding method is proposed to further improve the localization performance. In chapter 5, we propose three method to eliminate the issues on CAM level. Our methods are evaluated on CUB-200-2011 and ILSVRC 2016 datasets. Experiments demonstrate that the proposed methods work very well and significantly improve the localization performance.


identifier: HosseiniHaghighi, SeyedehRabeeh  (2021) Characterizing and Structuring Urban Data for Housing Stock Energy Modeling.  Masters thesis, Concordia University.

abstract:
Setting Canada on a net-zero emission pathway by 2050 encouraged the current research to identify a workflow to focus on housing stock energy modeling by addressing the gap between the accessible urban datasets and the parameters required for building energy performance simulation. Urban building energy modeling (UBEM) supports policymaking for retrofitting buildings toward location-specific, low energy, and low carbon possibilities. The study deals with UBEM data management based on real urban datasets and characterizing archetype profiles to develop a bottom-up model capable of evaluating district energy scenarios. The different origins of datasets from multiple sources and scales required using a range of tools for data processing and analysis to synchronize with the UBEM specification and the CityGML geometry standard. The simulation platform SimStadt was used to integrate the city model with the developed archetypes in eight identified vintages for low-rise housing and estimate the district heating load.
A case study was carried out for the city Kelowna in BC /Canada. The average simulated heating energy use intensity showed almost 10% deviation from the national measured data in British Columbia. Furthermore, the model calculated the equivalent CO2 emission as well as the district's potential for on-site power generation combining photovoltaics with demand-side management. On the urban data side, the key barriers were the low compatibility between different urban datasets, lack of building identifiers shared between documentation conveying building information and deriving urban building geometry from data sources with low accuracies. Concerning the building energy input, the availability of characterized archetypes and local metered data would enhance the developed workflow and outputs toward effective energy policy and bottom-up retrofit planning.


identifier: Jagpaul, Puneet ORCID: https://orcid.org/0000-0002-6026-9664 <https://orcid.org/0000-0002-6026-9664>  (2021) Free Vibration Analyses of Stationary and Rotating Tapered Composite Beams with Delamination.  Masters thesis, Concordia University.

abstract:
ABSTRACT
Free Vibration Analyses of Stationary and Rotating Tapered Composite Beams with Delamination
Puneet Jagpaul
The exceptional engineering properties and customizability of the laminated composites have enabled their use in the design of the stationary and rotating tapered structures in the aerospace and energy sectors. The tailoring capabilities of the composite material can be used to stiffen the structure at one location while being flexible at other location and consequently reduce the weight, as required in specific applications such as helicopter rotor blade, windmill blade and turbine blade. The vibration characteristics (natural frequencies and mode shapes) of the stationary and rotating structures differ substantially and must be well identified in the design stage. The composite structures are prone to failures such as delamination and fiber-matrix debonding caused during their fabrication or in service, especially when used as blades and beams in various stationary and rotating applications. Delamination reduces the overall stiffness and the strength of the laminates, which may lead to local or sudden structural failures. The delaminated structure has reduced natural frequencies and exhibits different mode shapes than that of the intact structure.
In the present thesis, the free vibration analyses of stationary and rotating tapered composite beams with delamination are conducted. The influence of the delamination on the vibration characteristics of the stationary and rotating tapered composite beams is comprehensively studied. The Finite Element Analysis tool ANSYS® is used to develop three-dimensional models of the intact and delaminated composite beams. The natural frequencies of the stationary and rotating intact cantilever composite beams are determined for uniform, thickness-tapered and doubly tapered beam profiles using modal analysis and the results are compared with the results available in the literature. The Mode-I and Mode-II delamination tests are performed on the numerical models of the double cantilever beam and end notch flexure test samples based on cohesive zone modeling and the results of the tests are verified with the available results. The critically stressed locations prone to delamination in the stationary and rotating composite beams are determined using the first-ply failure analyses based on Tsai-Wu failure criterion. The free vibration responses of the stationary and rotating composite beams with end and mid-span delaminations of different lengths and with different stacking sequences are obtained and they are verified wherever possible. The delamination length that has minimal effect on the first three natural frequencies of the uniform and thickness-tapered composite beams is determined and is found to be 5% of the total beam length. Higher modes should be investigated for the composite structures with smaller delamination. A basis for the non-destructive evaluation is suggested for the stationary thickness-tapered simply supported composite beams with end and mid-span delaminations. The influences of the delamination length, delamination location, fiber orientation angle, thickness-tapering, double tapering, layer reduction and taper angle on the free vibration response of the stationary and rotating delaminated composite beams are investigated for uniform, thickness-tapered and doubly tapered beam profiles through various parametric studies. The influences of the rotational velocity and hub radius on the natural frequencies of the rotating doubly tapered composite beams with delamination are thoroughly examined. The present thesis contributes towards the safe design of the composite structures. The studies performed are helpful for developing delamination detection techniques based on the free vibration response of tapered composite beams and can aid designers to model optimised tapered composite structures by considering the influences of delamination on their vibrational characteristics.


identifier: Bregu, Ornela ORCID: https://orcid.org/0000-0001-8337-2376 <https://orcid.org/0000-0001-8337-2376>  (2020) Mixture-Based Clustering for High-Dimensional Count Data Using Minorization-Maximization Approaches.  Masters thesis, Concordia University.

abstract: The Multinomial distribution has been widely used to model count data. To increase clustering efficiency, we use an approximation of the Fisher Scoring as a learning algorithm, which is more robust to the choice of the initial parameter values. Moreover, we consider the generalization of the multinomial model obtained by introducing the Dirichlet as prior, which is called the Dirichlet Compound Multinomial (DCM). Even though DCM can address the burstiness phenomenon of count data, the presence of Gamma function in its density function usually leads to undesired complications. In this thesis, we use two alternative representations of DCM distribution to perform clustering based on finite mixture models, where the mixture parameters are estimated using minorization-maximization algorithm. Moreover, we propose an online learning technique for unsupervised clustering based on a mixture of Neerchal- Morel distributions. While the novel mixture model is able to capture overdispersion due to a weight parameter assigned to each feature in each cluster, online learning is able to overcome the drawbacks of batch learning in such a way that the mixture’s parameters can be updated instantly for any new data instances. Finally, by implementing a minimum message length model selection criterion, the weights of irrelevant mixture components are driven towards zero, which resolves the problem of knowing the number of clusters beforehand. To evaluate and compare the performance of our proposed models, we have considered five challenging real-world applications that involve high dimensional count vectors, namely, sentiment analysis, topic detection, facial expression recognition, human action recognition and medical diagnosis. The results show that the proposed algorithms increase the clustering efficiency remarkably as compared to other benchmarks, and the best results are achieved by the models able to accommodate over-dispersed count data.


identifier: Shaik, Rizwan Ahmed  (2021) Influence of Strain Hardening on the Water Droplet Erosion Performance of 17-4 PH Stainless Steel.  Masters thesis, Concordia University.

abstract:
Water Droplet Erosion (WDE) is a wear erosion phenomenon that is predominantly observed in gas, steam and wind turbines due to repetitive droplet impacts. In this work, various damage mechanisms pertaining to this phenomenon, described in the literature, are reviewed in detail. It was found that various surface treatments have been applied to delay the start of erosion in the material. However, in doing so the role of strain hardening was not well understood.
In this work, a suitable material is identified to study the effect of strain hardening on the WDE performance. The material was characterized for various mechanical properties and for water droplet erosion. The material was also tested for WDE by performing a Deep Rolling (DR) treatment before testing. The erosion incubation time is analyzed by considering the yield strength, elastic resilience and strain hardening exponent. It was found that the erosion incubation time is dependent on the yield strength, elastic resilience and strain hardening exponent of the material.
The role of strain hardening on WDE performance was also studied by intermittent strain relieving of the samples exposed to WDE. The frequency of strain relieving was found to influence the erosion behavior. It was observed that frequent strain relieving during WDE influences the erosion incubation time and the maximum erosion rate.


identifier: Maertens, Catherine  (2021) La réception des revendications autonomistes des Inuit du Nunavik par les partis souverainistes au Québec.  Masters thesis, Concordia University.

abstract: Cette recherche porte sur la réception des revendications autonomistes des Inuit du Nunavik par les partis souverainistes au Québec. L’objectif est d’analyser les changements dans les discours des partis politiques souverainistes à travers leurs interactions et leur positionnement face aux revendications politiques des Inuit du Nunavik. Le premier volet vise à documenter et visibiliser les voix autonomistes des Inuit du Nunavik et leurs relations avec le gouvernement québécois depuis les années soixante. Le second volet analyse l’évolution des discours des acteur-trice-s politiques souverainistes au Québec en tentant de comprendre quelles rhétoriques perdurent et quels sont les discours émergents selon les affiliations politiques des participant-e-s. L’analyse qualitative se base sur quatorze documents d’archives témoignant d’événements impliquant le Parti Québécois et les groupes autochtones entre 1978 et 1983. Six différentes tangentes discursives sont d’abord identifiées, soit le mea-culpa, la justification, le rapprochement, la normalisation, l’obstacle, ainsi que le maintien de l’intégrité. Ces tangentes discursives sont ensuite analysées en parallèle avec le discours de six politicien-ne-s de diverses formations politiques souverainistes actuelles telles que le Parti Québécois, Québec solidaire et le Bloc Québécois afin de constater quelles tangentes discursives ont traversé l’épreuve du temps. Les nouveaux thèmes qui apparaissent dans les discours souverainistes contemporains sont également présentés. Ainsi, cette recherche tente de comprendre comment ont évolué certaines rhétoriques indépendantistes propres au colonialisme de peuplement. Une réflexion théorique sur notre rapport au territoire et son impact sur l'autodétermination des peuples clôt ce mémoire.