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Decentralized and Intelligent Estimation: Theory and Applications
No full textContemporary technological development has had a profound impact on the architecture and operation of modern systems. In particular, smart systems, defined by their capacity for adaptation, have emerged as a dominant paradigm across various sectors. This dissertation presents two complementary surveys that establish the conceptual foundation for the technical contributions that follow. The first is a comprehensive examination of smart system architectures, framed through the lens of cognitive dynamic systems, which decomposes smart systems into five core components: control, perception, knowledge, communication, and security. The second is a focused survey on Intelligent Estimation, which explores the intersection of estimation theory and learning-based systems.
Motivated by the increasing reliance on secure and distributed inference, the first technical contribution introduces Decentralized Estimation (DeEst), a novel data-driven decentralized estimation framework that integrates data-driven local inference with blockchain-based federated consensus. In DeEst, each node maintains a local estimator informed by historical observations and contributes parameter updates to a shared global model via a blockchain-federated learning protocol. This architecture eliminates the need for a central aggregator while ensuring robustness to communication failures, malicious nodes, and node data heterogeneity. The second contribution focuses on estimator robustness at the node level through the development of the Sliding Sigmoid Filter (SSF), an extension of the Sliding Innovation Filter (SIF). By incorporating a nonlinear sigmoid-based saturation function, the SSF enables smoother transitions across innovation magnitudes, improving estimation stability in the presence of abrupt deviations or measurement outliers. The SSF’s capacity to modulate updates adaptively makes it particularly well-suited for decentralized implementations, where maintaining local estimator reliability in the face of system faults is essential to ensuring system-wide accuracy. The final contribution presents a novel learning paradigm, referred to as Intelligent Estimation, which reinterprets neural network training as a probabilistic filtering problem. In contrast to conventional gradient-based optimizers such as SGD or Adam, which often suffer from poor convergence in noisy settings, Intelligent Estimation employs estimation methods, such as the SSF, to adaptively scale weight updates based on innovation magnitudes, enabling context-aware and noise-resilient learning. The approach is empirically validated across diverse benchmark datasets, demonstrating improvements in both convergence behavior and generalization performance.ThesisDoctor of Engineering (DEng
Innovation effects of information and communication technologies: Evidence from Canadian firms
No full textThis paper offers empirical evidence that Information and Communication Technologies (ICT) significantly boost both product and process innovation across Canadian industries. Using longitudinal data from the Canadian Workplace and Employee Survey (1999–2005), the study finds a positive, significant link between ICT adoption (measured by computer usage) and four types of innovation: new products, improved products, new processes, and improved processes. From a policy standpoint, the findings highlight the value of supporting ICT adoption to drive innovation and productivity. Two mechanisms are identified: (1) direct investment effects via reduced ICT costs, and (2) indirect spillover effects through organizational and knowledge transformation
Double Exponential Cubature Kalman Filtering
No full textGaussian filtering supports many estimation tasks, yet real systems present nonlinearity, outliers, and model mismatch. This thesis advances the methodology and practice of such filters in two parts. First, it develops the Double Exponential Cubature Kalman Filter (DECKF), which evaluates Gaussian-weighted moments using a double exponential cubature rule with positive weights and a scalable point set. The analysis clarifies accuracy and stability as the number of cubature points grows, observes positive-definiteness behavior in the prediction and update steps, and provides tuning guidance that accommodates cubature point count, process and measurement covariances, and numerical conditioning. An additional robust correction strategy, the Double Exponential Sliding Innovation Filter (DE-SIF), constrains the measurement update within a sliding boundary layer to limit the influence of abnormal innovations while preserving the standard Kalman structure and compatibility.
Second, the thesis studies performance in a demanding condition monitoring problem. The DECKF is combined with an interacting multiple model framework and is compared against the EKF and UKF on a mode-switching magnetorheological damper governed by Bouc-Wen dynamics. The study quantifies force-estimation accuracy, correlation with reference force, detection performance across operating modes, and statistical consistency via normalized innovations and related tests. Results show that the IMM-DECKF delivers strong force tracking and consistent innovations with competitive detection performance, and that its benefits grow with careful cubature point selection and covariance tuning.
Beyond the specific damper experiment, the proposed DE cubature rule and sliding innovation strategy apply to broader estimation tasks where Gaussian filters are standard, including target tracking, navigation, and control, and offer practical guidance on stability, tuning, and diagnostics.The work presented in this thesis was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) through Alliance grant ALLRP 561511-20
WAVEFORM DESIGN FOR MONOSTATIC DOWNLINK INTEGRATED SENSING AND COMMUNICATION SYSTEMS
No full textWith the opportunities provided by higher frequencies, larger bandwidths, and intelligence, Integrated Sensing and Communication (ISAC) is widely recognized as one of the new applications that will drive the development of future generations of wireless networks. This thesis focuses on dual-function radar-communication systems, in which a single waveform is synthesized to achieve both the communication and sensing functions. The thesis develops design techniques for that waveform, aiming to jointly optimize communication and sensing performance, under practical constraints that facilitate implementation. A progressive three-part framework is proposed, covering robust extended linear precoding, hybrid linear-nonlinear precoding, and unstructured direct waveform design.
First, to address the sensitivity of the extended linear precoding scheme to imperfect knowledge of the environment, in Chapter 2 we develop a robust design that seeks jointly optimal transmit and radar receive beamformers in the presence of uncertainty. The method maximizes the worst-case Signal-to-Interference-plus-Noise Ratio (SINR) in the radar return signal, while ensuring communication users meet their SINR targets with a given probability of outage. Numerical results show that our proposed method can achieve better performance than approaches that are based on heuristic modifications of designs that assume perfect knowledge of the environment.
The extended linear precoding architecture used in the robust design facilitates design techniques that are based on statistical models for the communication symbols. That is sufficient for design objectives that are functions of the transmit covariance. However there are several important sensing objectives and implementation constraints that are functions of the waveform itself, and not simply its covariance. In scenarios where those objectives and constraints are important, nonlinear precoding has the potential to provide significantly better performance. The existing approaches to nonlinear precoding take a block-by-block symbol-dependent design approach, and may require adaptation of the communication receivers in each symbol block. Therefore, in Chapter 3 we develop a design technique for hybrid linear-nonlinear precoders (HLNP) that fuses the operational simplicity of statistics-based design of linear precoders and the degrees of design freedom provided by symbol-dependent nonlinear precoding. We evaluate this design approach using a problem that seeks to minimize a simplified Cramer-Rao bound on angle estimation of multiple point targets. Our experimental results show that the proposed method achieves essentially the same performance as an existing symbol-dependent hybrid linear-nonlinear precoding, while being able to directly control the transmitted waveform and maintaining receiver adaption on the time scale of environment coherence time.
Finally, in Chapter 4 we introduce a new approach to unstructured direct waveform design. Unlike existing approaches, which require the receivers to have fixed equalizers, or to update the equalizers for every data block, the proposed design allows the equalizer at each receiver to be adapted at the scale of the coherence time, using the conventional dedicated downlink training, while maintaining the ability to explicitly control the transmitted waveform. In an example employing sensing objectives obtained from a Bayesian Cramer-Rao bound, the proposed approach demonstrates performance that is close to the methods with equalizer adaption at the time scale of the data block, better than the methods with constant equalizers, and better than symbol-dependent linear precoding techniques
REFERRAL PATTERNS OF PRIMARY CARE PRACTICES TO SPECIALIST PHYSICIANS AND LABORATORY MEDICINE SERVICES IN ONTARIO, CANADA
No full textBackground: Primary care physicians (PCPs) are critical to Ontario’s health care system, acting as the first point of contact for patients with the system. They play a critical role in facilitating referrals to specialists and laboratory services, as part of clinical decision-making to address patients’ health care needs. However, there is limited understanding of how different primary care practice models impact different aspects of referrals, such as rate of referrals to specialists, communication with specialists about their referrals, and rate of referrals to laboratory medicine services, particularly within the context of Ontario’s primary care reform. This thesis aimed to comprehensively study primary care physician referrals to specialists and laboratory services and examine the association between their practice model and referral rates to specialist services and laboratory medicine.
Methods: This thesis includes three independent studies using quantitative observational research methods. Primary care physicians practicing comprehensive care were identified from health administrative databases, and their data was linked to physicians’ billing data (Ontario Health Insurance Plan), population-level patient experience survey data (Health Care Experience Survey) and other health administrative databases. Statistical analyses were conducted to examine the association between primary care physician’s practice models and referral rates to specialist and laboratory medicine services, adjusted for other physician, patient and practice-level factors.
Results: The first study showed that primary care physician referrals to specialists vary by practice model and sex. Those in predominantly fee-for-service models referred fewer patients to specialists than those in Family Health Teams (FHTs), Ontario's largest team-based care model. The second study showed that while patients generally across all models reported a high level of information coordination between their primary care physician and specialist, patients rostered to predominantly fee-for-service models were more likely to report that the specialist did not receive the necessary medical information from their primary care physician. The third study found that primary care physicians in FHTs had a lower rate of referrals to laboratory services than those in other primary care practice models.
Conclusion: Primary care physician practice models significantly influenced rates of referrals to specialists and laboratory medicine services. Primary care physicians in FHTs had lower referral rates for laboratory services and higher coordination of information with specialists, they had a higher referral rate to specialists and to different subspecialties. These findings emphasize the importance of considering the impact changes to primary care practice models could have on the utilization of specialist and laboratory medicine services as Ontario continues to reform the primary care system and expand team-based care models such as FHTsThesisDoctor of Philosophy (PhD)Primary care physicians are the first point of contact in Ontario's health care system, and their collaboration with specialists and laboratories is critical for patient care. However, there is a limited understanding of how their practice model influence referrals to specialists, communication with specialists about their care, and referrals to laboratory medicine services. This thesis examined the association between primary care physicians’ practice models and different aspects of referrals using population-level health care data. The results showed that referral patterns vary widely depending on the primary care physician's practice model. Physicians in Family Health Teams, Ontario's largest team-based care model, had lower lab referral rates and better communication with specialists than other models. However, their referral to specialists was higher. These findings suggest that future changes to primary care practice models, including expansion of Family Health Teams, should carefully consider their impact on increased health care utilization, particularly on specialist and laboratory services
Exploring the sexual and reproductive health of 1.5-generation Bangladeshi women in Toronto, Ontario
No full textThis doctoral dissertation, comprised of four papers, explores the sexual and reproductive health (SRH) of 1.5-generation Bangladeshi women in Toronto, Ontario. The “1.5 generation” refers to those who immigrated to the destination country as children. The cross-cultural positionality of 1.5-generation Bangladeshi women has implications for their SRH as they navigate different cultural norms of their country of origin and destination. The objectives of this dissertation were to gain an understanding of the different dimensions of SRH of 1.5-generation Bangladeshi women, and the scope and nature of SRH interventions targeting young women in Canada. Narrative inquiry and scoping review methods were employed. In-depth semi-structured interviews were conducted with ten 1.5-generation Bangladeshi women aged 18-22, and peer-reviewed and grey literature were analyzed to collate evidence on SRH interventions targeting young women. Paper One explored the state and determinants of sexual and reproductive health and rights (SRHR) knowledge of 1.5-generation Bangladeshi women, and their experiences with school-based sex education in Canada. Findings showed that SRHR knowledge formation is a multidimensional, dynamic process whereby social identities (e.g., ethnicity, gender) intersect and operate within a larger social context. Paper Two investigated participants’ SRH-related help-seeking behaviours and perspectives and experiences with SRH services. The results underscored the influence of social and cultural factors on help-seeking behaviours and the barriers and facilitators in accessing SRH services. Paper Three explored participants’ dating practices in the context of the sociocultural restrictions around pre-marital relationships. The findings offer a nuanced understanding of the dating practices of 1.5-generation Bangladeshi women and the implications for access to SRH services. Finally, Paper Four revealed gaps in SRH programming for young South Asian women in Canada. Overall, this dissertation contributes to the sociological health literature by providing rich data on the SRH of 1.5-generation Bangladeshi women and highlighting gaps in education, services and programming.DissertationDoctor of Philosophy (PhD
What Is a Ἰουδαῖος? A Linguistic Investigation of Ἰουδαῖος’s Meaning and John’s Motivation behind his Peculiar Modulation
No full textThis study addresses the questions, What is a Ἰουδαῖος? and Why John’s Ἰουδαῖοι?, by employing a linguistic methodology to investigate both the systemic meaning potential of Ἰουδαῖος and the Evangelist’s motivation behind its distinctive modulation throughout his Gospel. Drawing on a register-balanced corpus of Hellenistic Greek texts, the research abstracts the term’s context-independent meaning—termed "Judahness"—and analyzes how this meaning potential is pragmatically realized in John’s narrative. Rather than assuming a single, fixed meaning governs all instances, this study demonstrates that Ἰουδαῖος exhibits great contextual adaptability, with its sense, referent, and appraisal modulated according to the Evangelist’s rhetorical and theological aims. In terms of referent, Ἰουδαῖος identifies a broad spectrum of individuals and subgroups within the larger group known as “the Jews,” from religious leaders to the Jewish crowd, and even specific individuals, from those who oppose Jesus to those who believe in him. Regarding appraisal, the use of Ἰουδαῖος in the Gospel shows diverse tones: sometimes carrying negative connotations, suggesting opposition or skepticism toward Jesus; at other times, imbued with positive connotations, indicating acceptance or belief; and in many instances, used neutrally, without any particular emotional charge. This pragmatic flexibility challenges reductive interpretations of the Gospel’s portrayal of the Ἰουδαῖοι and resists claims of uniformity in John’s depiction. Instead, the study argues that John’s usage is motivated by a twofold purpose: first, an evangelistic intent to reach a diverse Jewish audience; and second, an apologetic concern to demonstrate that Jesus fulfills all Jewish messianic hopes. This nuanced application of Ἰουδαῖος thus serves not only to convey John’s theological message but also to engage his intended readers in a discourse about identity, faith, and the true essence of Judaism as seen through the lens of Jesus’ messiahship
Selenium and Placental Trophoblast Cell Health
No full textCoal mining accelerates the release of selenium (Se) into the environment, where it
bioaccumulates through the food chain and increases human exposure. Se is an essential trace
element, but Se deficiency and Se excess have been associated with adverse pregnancy outcomes
linked to placental dysfunction. Cell culture studies show that Se can increase reactive oxygen
species (ROS) in placental trophoblast cells, potentially impairing cell health. This study
explored the effects of Se exposure on placental trophoblast cell health and tested the hypothesis
that NaSe exposure induces ROS accumulation, leading to reduced placental cell health. This
thesis also investigated if ferroptosis, cellular senescence, or apoptosis are induced following
exposure to Se and the mechanisms underlying these effects.
HTR-8/SVneo cells, a placental trophoblast cell line, were treated with environmentally relevant
sodium selenite (NaSe) concentrations (0.1, 0.2, 0.5, 1, 2 µM) for 24 hours. ROS production and
mRNA expression of genes related to ferroptosis, senescence, and apoptosis were measured. I
evaluated key components of ferroptosis (cellular iron content, the accumulation of
malondialdehyde, and LDH release), senescence (ß-galactosidase staining), and apoptosis
(TUNEL-based assay) using commercially available kits. To explore mediators underlying
apoptosis, I assessed ER stress using an inhibitor experiment, followed by assessing the effect of
ER stress on angiogenesis.
NaSe treatment at the highest concentration (2 µM) caused a significant increase in ROS
production alongside altered mRNA expression of key markers indicative of ferroptosis,
senescence, and apoptosis. However, NaSe treatment did not affect functional measures of
ferroptosis or cellular senescence. 2 µM of NaSe increased apoptosis, an effect which appeared
to be related to increased gene expression of ER stress markers ATF4 and CHOP. To confirm NaSe could directly increase ER stress, cells were co-treated with 4-phenylbutyric acid (4PBA),
an ER stress inhibitor. 4PBA blocked the NaSe-induced increase of ATF4 and CHOP. Despite
the increase in ER stress, NaSe treatment did not affect angiogenesis. Given the rise in
anthropogenic activities is increasing our exposure to Se, further research is needed to
understand the mechanisms by which increased Se impacts mammalian reproductive function.ThesisMaster of Science in Medical Sciences (MSMS)Selenium (Se), a naturally occurring trace element, is required for key physiological functions
like antioxidant defense, but too much Se can have negative effects on health. Coal mining
activities can accelerate the release of Se into the environment; this has been linked adverse
reproductive outcomes in fish and wildlife, but the effect of high Se exposure on human
reproductive function is unclear. This study explored how Se affects the placenta, a critical organ
during pregnancy. Using placental cells, we tested different concentrations of Se and measured
its effect on cell health and function. Increased Se exposure generated reactive oxygen species
and triggered apoptosis, a form of programmed cell death. Further, it increased gene expression
of endoplasmic reticulum (ER) stress markers, which we could inhibit, confirming Se’s ability to
promote ER stress. These findings explain how increased Se may harm placental health and
contribute to adverse pregnancy outcomes
A Study of the Thermal Performance of Short-Term Thermal Storage Using Phase Change Materials in Integrated Community Energy and Harvesting Systems
No full textThermal energy storage systems are essential for bridging mismatches between energy supply and demand, with sensible storage in water tanks being the most common storage medium. In large community systems, however, the size of these tanks becomes a major limitation. Integrating phase change materials (PCMs) into water tanks has emerged as a promising solution to overcome this challenge, as PCMs can significantly increase storage density by utilizing latent heat. The benefit of the latent heat energy storage is, however, hindered by the low specific heat of PCMs relative to water. Moreover, PCMs typically have low thermal conductivity, which influences heat transfer performance. As such, careful design of hybrid water-PCM tanks is required to ensure that the full latent heat capacity is utilized and that high energy density (relative to water alone) is achieved.
The design of hybrid water-PCM tanks requires a systems context since the energy storage within the tank is determined by the operating temperature variations of the system. For example, because of the relatively low specific heat of PCMs, the benefit of a hybrid tank is enhanced when the operating temperature variation is low. In addition, due to the low conductivity of the PCMs, careful design of the PCM module is necessary to ensure that the PCM fully melts (or solidifies) within the available charging (or discharging) time. There is thus a need for mathematical models that can accurately predict the heat transfer and phase change characteristics of PCM modules while maintaining computational efficiency to allow for their incorporation into system analysis computer codes. The application of PCMs in long-term simulations, such as in community heating networks coupled with borehole fields, has been hindered by the computational cost of existing models which remain too expensive for simulations spanning months or years. This research addresses that gap by developing a reduced hybrid PCM–water tank model that is both accurate and computationally efficient, enabling the integration of PCM modules in community-scale energy systems to be studied in realistic, long-duration scenarios.
This thesis presents a new reduced-order PCM model for spherical encapsulations. The model builds on the quasi-stationary approximation but introduces an effective-latent-heat formulation that captures both sensible and latent contributions. This modification significantly improves accuracy while reducing computational demand by up to two orders of magnitude compared to enthalpy-based models. The reduced PCM model was verified against a detailed benchmark conduction-dominated enthalpy model that is validated with experimental data from the literature. It was then integrated into a stratified tank framework, producing a reduced hybrid water-PCM tank model that is accurate, efficient, and suitable for long-duration simulations. To facilitate practical use, the model was implemented into the commercial code TRNSYS as a new component, Type 250, and applied in the context of integrated community energy systems to investigate the impact of adding PCM spheres to the water tank integrated with a borehole field thermal storage system.
Parametric studies were performed on a hybrid water tank, revealing that its performance is strongly dependent on design and operating conditions. Higher mass flow rates shortened charging and discharging times but did not alter the total stored energy. Smaller spheres improved the melting rate, while larger capsules slowed it down. Lower temperature differences enhanced the PCM's latent heat contribution, increasing storage density but also extending charging times. Doubling the tank volume doubled the storage capacity, but it required higher flow rates to achieve a similar charging time. To guide system designers, a dimensionless contour map of PCM energy gain was developed, providing a simple tool for estimating the impact of capsule size, flow rate, and operating temperatures on the utilization of PCM.
The reduced hybrid tank model was also applied to a community-scale Integrated Community Energy system with combined heat and power (CHP) units, short-term storage tanks, and a borehole field seasonal thermal storage. The results showed that PCM integration increased both the energy transferred to the borehole and the useful energy recovered from the CHP, especially at low CHP supply temperatures (i.e., 50°C). At higher CHP supply temperatures, the benefit of PCM diminished because most of the stored energy was in the form of sensible heat rather than latent heat. Notably, a 2 m³ tank with 50% PCM achieved higher energy density than a 4 m³ water-only tank, demonstrating the clear advantage of PCM integration in reducing the required tank volume. PCM also improved borehole performance by raising the average storage temperature, which enhanced the coefficient of performance of heat pumps and reduced compressor work during discharge.
In summary, the contributions of this work include a new reduced PCM model that captures both sensible and latent heat while remaining highly computationally efficient; the development of a hybrid PCM–water tank model suitable for annual system simulations at low computational cost; the implementation of a new TRNSYS component (Type 250) to integrate the model into a widely used simulation platform; and the creation of a dimensionless contour map as a design tool for quickly estimating PCM performance under varying conditions. Finally, through a system-level case study, it demonstrated the tangible benefits of PCM integration in terms of tank storage density, CHP utilization, and borehole field performance, effectively overcoming the major barrier of high computational cost in detailed PCM models and enabling realistic deployment of PCM-enhanced hybrid tanks in community-scale energy systems.ThesisDoctor of Philosophy (PhD