21793 research outputs found
Sort by
The Effects of Self-Quantification on Consumer Well-Being
No full textIn two essays, this dissertation aims to explain the complex impact of self-quantification on consumer well-being related to body image. It also proposes interventions to mitigate its negative influence while preserving its benefits.
Given that the impact of self-quantification on self-objectification remains empirically understudied, the first essay addresses this gap by identifying conditions that amplify this relationship. Drawing on self-determination and internalization theories (Deci & Ryan, 1985, 2002; Grolnick, Deci, & Ryan, 1997), two cross-sectional studies reveal that self-quantification is positively associated with self-objectification, particularly among individuals with low levels of controlled motivation (i.e., motivation driven by external or internal pressure). Moreover, appearance-ideal internalization mediates this relationship, suggesting that self-quantification may trigger the internalization of societal beauty standards, which in turn fosters self-objectification. These findings provide insights into the psychological consequences of self-quantification and offer practical implications for technology developers aiming to balance its benefits and risks for consumer well-being.
Building on the mixed findings in the literature, the second essay investigates the dual effects of self-quantification on body-image related well-being through the lens of objective self-awareness theory (Duval & Wicklund, 1972; Silvia & Duval, 2001). It also evaluates the effectiveness of mindfulness-based interventions in reducing its adverse effects. A cross-sectional study shows that data interpretation tendency moderates the relationship between self-quantification and worsening body image, such that individuals with high self-criticism or low self-knowledge are more likely to experience greater body shame and appearance anxiety. Furthermore, two longitudinal experiments demonstrate that the proposed intervention (i.e., focus on emotions following exercise or dietary self-quantification) reduces negative outcomes (e.g., contingent self-worth, body shame, and appearance anxiety) while enhancing positive outcomes, including body appreciation and self-compassion. These findings contribute to the growing discourse on self-quantification by offering theoretical insights into its complex psychological effects and by proposing practical strategies to promote greater consumer well-being.
Overall, this dissertation advances understanding of the complex impact of self-quantification on consumer well-being associated with body image and provides actionable strategies for consumers and developers of self-quantification technologies to promote health and well-being
A Control Framework for Enhancing Vulnerable Road User Awareness in C-V2X Networks
No full textWireless device-to-device (D2D) communications over 5G, and Beyond 5G (B5G) open new possibilities for Intelligent Transportation Systems (ITS). New multiple-access schemes support reliable safety applications, including proximity, turn alerts, and crash prevention. These emerging technologies promise to transform transportation safety and efficiency.
In this thesis, the design and implementation of a control system based on a new VRU-centered approach is proposed to serve adaptive ITS safety applications to consider and increase Vulnerable Road User (VRU) awareness from motor vehicles, without jeopardizing the network performance.
For this purpose, the VRU Awareness Probability (VAP) is defined and modeled over 5G New Radio (NR) to quantify the extent to which motor vehicles are aware of VRU. Subsequently, an analytical relationship is established between VAP and the key performance indicators of the ad-hoc communication network, which is based on results obtained from a simulation of an urban intersection scenario where users are connected through 5G NR technology using mode 2 for D2D communication. Later, the European Telecommunications Standards Institute (ETSI) clustering algorithm was implemented over simulations on VRU, and the impact of this scheme on the network key performance indicators (specifically, the Packet Delivery Ratio (PDR)) and on the VAP was demonstrated, with an average increase of 50% and 65%, respectively
Digital Afterlife: The Physical and Digital Materiality of Urban Objects Captured through Photogrammetry
No full textThis thesis provides a comprehensive investigation into digital material and the 3D photoscanning process. It argues for an emotional investment in the treatment of the inanimate through a visual analysis of the material qualities of photoscanned objects. It highlights the photogrammetric process, leveraging it to explore an afterlife of these digitally reconstructed objects, which would otherwise occupy a space of abandon in the digital realm. Contrasting the pervasiveness of high-quality, clean assets, it elevates digital objects wrought with glitches, distortions, and imperfections, all bestowed on them as a product of the processes involved in their creation.
The research establishes a history of the relevant tools and technologies before examining theories on objects and materials of both physical and digital nature. It surveys these theories and concepts through the practice-led computer-generated artwork Digital Afterlife, utilizing both the artwork and its creation process, from asset collection to display, to explore a narrative of care towards neglected objects
Impact of Pharmacological and Non-Pharmacological Interventions on Sleep and Cognition in Older Adults with Insomnia
No full textSleep supports overall health and cognition, notably memory consolidation through NREM-related brain oscillations. Sleep architecture is disrupted by aging, with chronic insomnia further compounding these changes. Given its links to cognitive decline and adverse health outcomes, addressing chronic insomnia in older adults is critical for promoting healthy aging.
High insomnia prevalence in older adults contributes to widespread sedative-hypnotic use, yet its impact on sleep regulation remains unclear. We compared sleep architecture, EEG spectrum, and NREM brain oscillations related to memory consolidation across older adults with chronic insomnia, with and without chronic sedative-hypnotic use (benzodiazepines, BDZ, and benzodiazepine receptor agonists, BZRA), and good sleepers. Findings indicated that chronic BZD and BZRA use impairs sleep regulation at both macro- and micro levels, potentially mediating the association with cognitive decline in aging.
Cognitive behavioral therapy for insomnia (CBTi) is a non-pharmacological intervention that constitutes the first-line treatment for insomnia. This study assessed the combined impact of CBTi and sedative-hypnotic withdrawal on sleep and cognition in older adults with chronic insomnia. The combined intervention improved withdrawal success, reduced insomnia severity, and preserved sleep duration, while also enhancing subjective sleep quality. A concurrent reduction in sleep spindle density was observed. These findings highlight strategies for safer and more effective sedative-hypnotic discontinuation in aging populations.
Rocking bed stimulation represents a promising intervention to improve sleep and memory, although its long-term effects remain unclear. This study examined the impact of three consecutive nights of rocking apparatus stimulation in young good sleepers to replicate prior findings, intended for future application in older adults with insomnia. On the first night, rocking stimulation did not enhance sleep architecture, brain oscillations, or memory, likely due to suboptimal motion and noise-related disturbances. However, a second night rescued some effects, suggesting rapid habituation. These findings underscore the importance of refining stimulation parameters to optimize the potential benefits of rocking on sleep and memory.
This thesis presents new insights into pharmacological, behavioral, and rocking motion interventions, which may help design a comprehensive approach to enhancing sleep quality and cognitive health in aging populations
Caught between hostile and hospitable: Navigating the challenging menopausal journey
No full textConsumer learning is often associated with positive experiences in marketing literature, where individuals voluntarily engage in acquiring a new consumption repertoire through market resources. In contrast, recent research has shown that learning can also occur in challenging scenarios, where individuals are forced to engage in an uncomfortable learning process, highlighting a clear division between hospitable and hostile environments. However, how do consumers learn in environments that offer both hostile and hospitable experiences? By studying the current menopause context in Canada, I investigate how individuals undergoing this physiological transition cope with uncomfortable bodily changes while engaging with a market that offers various learning resources. Drawing on in-depth interviews, passive netnography, archival data from Reddit forums, YouTube videos and podcasts, my findings reveal that complex vocabulary, idiosyncratic symptoms, diagnostic inaccuracy, and trial-and-error cycles shape the hostile menopause learning environment. Notably, in this environment, institutional resources from relevant health market actors emerge, offering both hospitable and hostile experiences to menopausal individuals. A similar duality is also observed among menopausal communities, where consumers connect to share experiences, seeking mutual support and additional learning resources. This research contributes to the literature on consumer learning, communities and market actors. From a practical perspective, the study also highlights issues in the current health care market and offers insights for both market actors and individuals navigating menopause
Transverse Slot Antenna with a Stepped Groove Gap Waveguide Feeding Network
No full textThis thesis investigates the performance enhancement of transverse slot antennas using Groove Gap Waveguide technology. It focuses on improving bandwidth, gain, and radiation characteristics for modern wireless communication systems, particularly in the sub-6 GHz and millimeter-wave bands for 5G and beyond. The study begins with a comprehensive review of GGW technology, Electromagnetic Band Gap structures, and slotted antenna designs, highlighting their significance in overcoming challenges such as high path loss, limited penetration, and narrow bandwidth in high-frequency applications.
A simple single GGW slotted antenna is designed and analyzed, operating in the 3.1–4.6 GHz range with an impedance bandwidth of 38%, achieving a highest gain of 7 dBi. To enhance performance, rectangular corrugations are incorporated into the top layer, extending the matching impedance bandwidth to 54% and a highest gain of 10.3 dBi is achieved by introducing a step under the slot at the GGW-to-slot transition, resulting in a remarkable 77% impedance bandwidth while maintaining a gain of 10.3 dBi. The measurement results closely align with simulations, demonstrating a 73% matching impedance bandwidth. The scalability of the stepped design is also explored, showing that the 77% impedance bandwidth is preserved when scaled to center frequencies of 30 GHz and 60 GHz, making it highly suitable for mm-wave applications.
Simulations using CST Studio and HFSS validate the designs, with detailed analyses of S_11, gain, radiation patterns, and E-field distributions. The results underscore the effectiveness of GGW technology, EBG structures, corrugations, and steps in addressing the limitations of traditional slotted antennas, offering a robust solution for wideband, high-gain antennas in next-generation wireless networks. This research contributes to advancing antenna design for 5G, radar, and satellite communications, providing a foundation for future developments in scalable, high-frequency antenna systems
A Relational Egalitarian Account of Contributive Justice
No full textThis paper advances a relational egalitarian account of contributive justice, arguing that individuals have a positive right to work certain kinds of jobs and a duty to contribute to others. I offer this account of contributive justice as either complementary to, or as a replacement for, existing liberal egalitarian accounts that focus on equalizing distributive shares of the benefits and burdens of working. The paper goes over some problems for these kinds of accounts before introducing a novel one, which takes as its starting point the claim that justice requires that individuals participating in a joint scheme of cooperation be able to relate to each other as equals
Neutral Plane in Single and Group of Piles in Clay Subjected to Direct and Indirect Loading
No full textABSTRACT
Neutral Plane in Single Pile and Pile Group in Clay under Indirect Loading
Mehrdad Ghavi,
Concordia University, 2025
Clayey soils pose significant challenges for geotechnical engineering due to their compressibility and tendency to undergo considerable settlement under loading or long-term consolidation. These soils may exhibit moderate strength initially but can soften over time, especially when subjected to changes in moisture content or sustained stress, potentially leading to excessive settlements and foundation performance issues. Pile foundations are commonly used to support structures in clayey soils; however, they are susceptible to the development of negative skin friction (NSF), particularly when interacting with soft or consolidating clay layers. This condition induces additional axial loads on the piles and may compromise the structural integrity of the foundation system.
This thesis investigates the behavior of pile foundations embedded in clay through detailed finite element analysis using Abaqus. The study focuses on the effects of pile group configuration—including pile spacing, pile diameter, pile length—the influence of soil strength and deformation properties, and loading conditions on the development of negative skin friction, total load capacity, and overall foundation performance. The analysis considers both single piles and groups of four piles arranged in different configurations. Several parametric studies were conducted to assess the sensitivity of these variables under various soil and loading condition.
A numerical model was developed and calibrated based on previous experimental findings and literature data to simulate the complex interaction between the pile and the surrounding soil. Special attention was given to modeling soil behavior before and after varying key parameters. Comparative analyses of different pile group arrangements were performed to evaluate group interaction effects and their influence on drag load distribution, load capacity, and settlement behavior.
The numerical results align well with findings from the literature and contribute to a deeper understanding of pile performance in clayey soils. Practical recommendations are proposed for optimizing group pile design in such conditions, aiming to enhance the safety and efficiency of foundation engineering in problematic ground environments
A Distance-Based Approach to Independent Component Analysis
No full textIndependent Component Analysis (ICA) is a widely used statistical technique for decomposing multivariate signals (mixtures) into their underlying (non-Gaussian) independent components. Mathematically, ICA models observations Y ∈ Rd, d ≥ 2, as a mixture of unobserved independent source components X ∈ Rd, via an unknown nonsingular mixing matrix A, namely, Y = AX. The goal of ICA is to estimate the unmixing matrix B = A−1 based on IID data Yi = AXi, i = 1, . . . , n; to separate the mixed signals into the underlying independent components.
Our work proposes a novel distance-based approach for estimating B. The estimation is performed by minimizing the distance ρw between the joint empirical distribution function of X1, . . . ,Xn, and the marginal empirical distribution functions of the coordinates. We establish that ρw is asymptotically a U-statistic and derive its theoretical properties. Further, we analyze the empirical process to derive an estimation strategy for B. We devise two separate methods to construct confidence intervals. The first one uses the U-statistic and a specialized weight function that makes it independent of the distributions of the sources. The second method relies on the principal components of the empirical process. To make this approach computationally feasible, we propose a Gradient Descent Algorithm (GDA) to compute the estimate, and demonstrate its effectiveness by comparing it to the prevalent FastICA method (cf. Hyvarinen and Oja (2000)).
This work contributes both theoretically and numerically to the field of ICA by introducing a new approach to the estimation problem as well as providing a practical algorithmic implementation procedure
Objective Criteria Formulation for Two-Sided Matching Problems Using Environment-Based Design and Natural Language Processing
No full textEvery day, people and organizations make decisions that involve multiple, often conflicting, criteria. The complexity of these decision-making problems arises from the need to balance competing factors such as fairness, efficiency, and individual preferences. This thesis focuses on two-sided matching (TSM), a particular multi-criteria decision-making (MCDM) problem central to fields like operations research and market design. In TSM systems, two distinct sets of agents—such as employers and job seekers, schools and students, or donors and recipients—seek to be matched with members of the other set. While most research addresses how to match agents, this thesis focuses on the underlying decision criteria by examining how the criteria can be defined in a way that is fair, complete, and free from bias considering all human factors in effect.
Traditionally criteria have been determined by expert opinions, surveys, or historical data. However, these methods may be biased, cannot escape from past inequalities and fail to capture the complete criteria. To address this limitation, this thesis proposes a novel interdisciplinary methodology that integrates Natural Language Processing (NLP), optimization theory, and engineering design science to discover criteria from human-centered problem descriptions. This approach extracts objective decision criteria from natural language descriptions of the matching problem in a systematic and inclusive way using environment-based design (EBD), environment-based life cycle analysis (eLCA), and recursive object model (ROM). The utilization of these engineering design methodologies allows for adaptive, domain-independent, and data-driven criteria formulation, eliminating the need for subjective inputs.
To demonstrate the effectiveness of the proposed method, the methodology is applied in both static and dynamic matching scenarios. Static matching refers to problems involving fixed sets of participants, while dynamic matching accounts for changing sets, such as time-based arrivals. For
iv
the static case, an assignment-based optimization model is used to generate matches based on the identified criteria. For the dynamic case, a perishable capacity management optimization model is adopted, allowing the system to handle uncertainty and last-minute changes effectively.
Key contributions of this research include: a domain-independent, adaptable, and automated methodology for discovering decision criteria in two-sided matching (TSM) problems—eliminating reliance on subjective bias; an original application of design science principles to TSM, framing decision-making as a contextualized, iterative process grounded in stakeholder needs and environmental understanding; a systematic, algorithmic approach for defining input parameters in multi-criteria decision-making (MCDM) optimization models, bridging natural language understanding and mathematical formulation; a significant advancement in fairness and transparency within TSM systems by ensuring that matching decisions are based on objective, inclusive, and human-centered criteria. By redefining how matching problems are formulated and solved, this research lays the foundation for more equitable, adaptive, and human-centered decision-making systems