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Recursive Parameter Estimation of Non-Gaussian Hidden Markov Models for Occupancy Estimation in Smart Buildings
Get PDFA significant volume of data has been produced in this era. Therefore, accurately modeling these
data for further analysis and extraction of meaningful patterns is becoming a major concern in a
wide variety of real-life applications. Smart buildings are one of these areas urgently demanding
analysis of data. Managing the intelligent systems in smart homes, will reduce energy consumption
as well as enhance users’ comfort. In this context, Hidden Markov Model (HMM) as a learnable
finite stochastic model has consistently been a powerful tool for data modeling. Thus, we have been
motivated to propose occupancy estimation frameworks for smart buildings through HMM due to
the importance of indoor occupancy estimations in automating environmental settings. One of the
key factors in modeling data with HMM is the choice of the emission probability. In this thesis, we
have proposed novel HMMs extensions through Generalized Dirichlet (GD), Beta-Liouville (BL),
Inverted Dirichlet (ID), Generalized Inverted Dirichlet (GID), and Inverted Beta-Liouville (IBL)
distributions as emission probability distributions. These distributions have been investigated due
to their capabilities in modeling a variety of non-Gaussian data, overcoming the limited covariance
structures of other distributions such as the Dirichlet distribution. The next step after determining
the emission probability is estimating an optimized parameter of the distribution. Therefore, we
have developed a recursive parameter estimation based on maximum likelihood estimation approach
(MLE). Due to the linear complexity of the proposed recursive algorithm, the developed models can
successfully model real-time data, this allowed the models to be used in an extensive range of
practical applications
Analyzing Effects of Large and Rare Events with an Augmented Synthetic Control Method
Get PDFThis dissertation consists of four chapters on applying the Synthetic Control Method to rare events with a significant impact. Initially pioneered by Abadie et Al., the Synthetic Control Method is a policy analysis tool developed to tackle the weaknesses of traditional policy analysis models such as the Difference-in-Difference. In the first chapter of this dissertation, this model is used to reconcile a recurring issue in the disaster literature: why some countries recover better than others from disasters and the role that political institutions play in this recovery. The results show that regulatory power is the most significant institutional quality variable that determines post-disaster recovery. Ranking in the top 30\% of countries regarding regulatory power is linked to GDP recovery rates from disasters that are higher than predicted GDP. The variable with the most negligible impact was corruption, as proxied by the corruption perception index. A 1-point increase in this index was linked to a 0.05\% increase in the recovery rates compared to predicted GDP. On the other hand, the degree of democratization or level of democracy is insignificant in determining the size or level of recovery. Finally, over five years after the occurrence of a disaster, countries that experienced negative recovery rates of GDP per capita had this value shrink by about 13\%. In contrast, countries with positive recovery rates of GDP per capita ended up with a GDP per capita ahead of its predicted value by 8\% over the same five-year period.
One of the most devastating disasters of the last 50 years is the COVID-19 pandemic that put the entire world at a standstill. The second chapter of this dissertation summarizes the literature surrounding anti-contagion policies and highlights a gap in the literature in untangling the impact of individual anti-contagion policies. This gap is tackled in the third chapter, which investigates the relative importance and impact of individual anti-contagion policies in reducing death rates in the United States. Restrictions on gatherings proved to be the most significant policy in reducing death rates, lowering them on average by four out 100,000 COVID deaths per day 60 days after the implementation of such a policy. School closings and public transportation closings were the least effective policies reducing death rates by 0.2 and 0.5 per 100,000 over the same period.
In the fourth chapter, the traditional Synthetic Control Method is modified to account for cumulative and interrupted events through the Multi Synthetic Control Method. This method is tested on previous examples used in the literature and is shown to be robust to uninterrupted events. When applied to anti-contagion policies in the United States, the Multi Synthetic Control Method finds that the standard Synthetic Control Method can underestimate the true impact of a policy by up to 150\%. The values obtained from the Multi Synthetic Control Method for the same event as compared to the base Synthetic Control Method were significantly different, ranging between 20\% to 150\% different in absolute value.
Significant improvements have been made to the original Synthetic Control Method since its inception. In this thesis, additional improvements are proposed to improve this method's accuracy. In the first chapter, a new method of selecting the vector of relative importance (known as the vector) is discussed. This method improves the accuracy of obtaining this vector for regressions where the variance of the treated variable and the number of co-factor variables are high.
The results of this dissertation show the ability of the Synthetic Control Method to tackle all kinds of policies. Policy-makers aiming to take on upcoming waves or different mutations of the COVID-19 virus should consider the effectiveness of different policies and the implication of their stringency in affecting death rates and economic variables, and the trade-off between them
The river meanders still: Curation as research-creation for an unknowable exhibition.
Get PDFThe canalized southernmost section of Wonscotonach (the Don River) in Tkarón:to (Toronto), also known as The Narrows, is a highly disturbed urban natural landscape. Following the 1886 Don Improvement Project, the Keating Channel, and today the Port Lands Revitalization and Flood Protection Project, these Lands have been harnessed and developed through settler colonization to tame and control the once-winding river. This research-creation—in the form of a curated online exhibition and written thesis—presents a critical (re)reading of the notion of improvement, becoming allied to the pre-colonial landscape and the knowledge it carried.
This exhibition and thesis develop the concept of the meander, inspired by the non-linear trajectory of the pre-canalized Don River, as a model for the curatorial. The curatorial process of improvement becomes a wall, and the river meanders still began before the global COVID-19 pandemic and, subsequently, was derailed in March 2020. The exhibition’s final form was unknowable throughout much of the curatorial process. Thus, following the meander as a research-creation technique, the curatorial process, exhibitionary structure, and content had to adapt through lingering uncertainty. This thesis, contributing to the theoretical and practical knowledge of research-creation, looks to intersections with the curatorial following the theoretical underpinnings of Erin Manning and Brian Massumi, Natalie Loveless and Stefanie Springgay and Sarah E. Truman. As a project untethered from institutional timelines and normative requirements to ‘know a project in advance,’ as well as the conventions of a physical exhibition, this research-creation manifested through process-led, creative and exploratory techniques (such as walking and drawing) and slowed pace allowed by the COVID-19 pandemic’s reframing of time. This research-creation exhibition and written thesis develop a responsive and resilient curatorial process deeply indebted to Land-based knowledge
Synthesizing and Characterizing Advanced Biodegradable Wound Dressings
Get PDFOver the past two decades, technological advancements have enabled the development of
incredibly stimulating and accessible medical devices; however, once these devices have become
widely available, issues related to the safe disposal of the used materials and devices have arisen.
Various materials are used to fabricate advanced medical devices, including polystyrene, polyvinyl
chloride, and nylon. However, these materials take a long time to decompose within a regular
ecosystem, and traditional recycling methods are often harmful to the environment. Despite efforts
to regulate the disposal of non-recyclable wound dressings, progress has been slow. Various
industries have developed innovative wound care products and environmentally friendly processes
in response to environmental regulations and global environmental awareness. The use of starchbased
biodegradable wound dressings can make a significant contribution to environmental
protection. An innovative casting approach with a short procedure duration has been developed
and applied to produce starch-based wound dressings in accordance with various formulations in
this dissertation research. The revised formulation reduces the use of components in the
conventional preparation approach. This dissertation also examined the incorporation of non-toxic
metal-oxide particles, such as zinc oxide, into wound dressings to enhance the physical, chemical,
and biocompatibility properties. The standard methodologies were used to evaluate their
characteristics to determine whether these materials are suitable for wound dressings. A
comprehensive investigation of these materials fundamental physical properties, including
mechanical strength, elongation-at-break, surface morphology (X-ray Spectroscopy (EDX), and
scanning electron microscopy (SEM)), water vapor transmission rate, swelling index, weight loss,
solubility, antibacterial activity (against Escherichia coli and Staphylococcus aureus), pH levels,
UV-Vis spectroscopy, and biodegradability, was conducted for this purpose. As a wound dressing
material, starch-based dressings demonstrate adequate degradation, water vapor transmission rate,
antibacterial activity, fluid absorption, and mechanical strength, which are all essential
characteristics. Finally, by employing the central composite design approach, a set of experiments
was further carried out to optimize the starch-based wound-dressing preparation formulas
Metabolism of microbiomes in a changing Arctic Ocean
Get PDFThe world’s oceans are of utmost importance for us humans: they are a source of food
and half of the oxygen we breathe, they act as climate regulators, trade routes, tourism attractions,
and harbor an incredible diversity of life. The Arctic Ocean represents a particular
ocean, with acute variations of temperatures, ice and solar radiation regimes throughout the
year, and a strong terrestrial signature imparted by its immense watershed. But the oceans
are now under threat of a changing climate. The polar oceans are especially susceptible to
these changes with already dramatic visible consequences. The most visible consequence in
the Arctic Ocean is a continuous loss of sea ice with impact on albedo, solar radiation regimes
on the water surface, phytoplankton growth and primary productivity. The Arctic is also receiving
increasing amounts of freshwater, leading to a freshening, disturbing the water column
stratification, and increasing the load of organic matter from terrestrial origin. All these perturbations
profoundly modify the sources and dynamics of organic and inorganic matter in the
Arctic Ocean, perturbing the Arctic Ocean biogeochemical cycles. Given that microbial life is
at the base of cycling this organic and inorganic matter, microbes play pivotal roles by controlling
biogeochemical cycles and forming the base of the food web. Specifically, the diversity
of metabolic processes carried out by microbes determines how they interact with and shape
their environment. Despite the importance of understanding microbial metabolism in a rapidly
changing Arctic Ocean, our knowledge of the microbial processes that distinguish the Arctic
Ocean from the rest of the global oceans and how they are linked to the changing Arctic Ocean
biogeochemical cycles is still very fragmented.
In this thesis, I undertook to address the lack of knowledge about the metabolism of the
Arctic Ocean microbiomes by tackling two fundamental questions: (i) What are the specificities
and phylogenetic diversity of microbial metabolism in the Arctic Ocean compared to the other
world oceans? (ii) What are the relationships between the Arctic Ocean microbial metabolic
specificities and their biogeochemical environment?
I first discovered that metabolic pathways for the degradation of aromatic compounds were
enriched and expressed in the Canada Basin of the Arctic Ocean compared to the rest of the
global ocean, in particular in the subsurface waters where organic matter of terrestrial origin
accumulates. The capacity to degrade aromatic compound from terrestrial origin was phylogenetically
concentrated in Rhodspirillales. These Rhodospirillales were enriched in aromatic
compound degradation genes compared to close relatives from other oceans and their geographic
distribution was restricted to the Arctic Ocean. These results suggest that the capacity to degrade
aromatic compounds of terrestrial origin may be an adaptive trait of some Arctic Ocean
microbial taxa. Furthermore, the aromatic-metabolizing bacteria may become more prominent
as organic matter inputs from land to ocean continue to rise with climate change, potentially
impact the Arctic Ocean biogeochemical cycles.
In the second part of this thesis, I focused on the metabolism of neutral lipids, used to accumulate
energy and carbon reserves. Within the global ocean, I discovered that the metabolism
of neutral lipids was enriched in the microbial communities of the Arctic Ocean. In the photic
zone, eukaryotic phototrophs dominated the synthesis of neutral lipids. I also discovered a
large diversity of bacterial taxa able to degrade but not produce neutral lipids, suggesting that
photosynthetic-based production of neutral lipids in eukaryotes may serve as an important carbon
source for the heterotrophic bacterial community. Bacteria were the main producers in the
aphotic zone and were equipped with a di↵erent set of enzymes targeting di↵erent compounds
depending on their location within the water column. This study shows that the storage of
neutral lipids may be a selective advantage for prokaryotes and picoeukaryotes in a context of
extreme variations in energy and nutrients sources such as in the Arctic Ocean. In addition,
I propose that, similarly to lipids from eukaryotic phototrophs sustaining the food web during
the summer months, neutral lipids from prokaryotic origin may play an important role in sustaining
the food web during the dark winter months.
Finally, I undertook a global ocean study to unravel the metabolic genes and pathways
favored by the microbiomes of the Arctic Ocean. I confirmed the importance of aromatic
compound degradation and neutral lipid metabolism. But I also uncovered a myriad of other
metabolic processes favored by the microbiomes of the Arctic Ocean compared to other oceanic
zones. In particular, in the photic zone of the Arctic Ocean, I discovered the prevalence of genes
and pathways involved in the metabolism of glycans that might be involved in cold adaptation
mechanisms. Importantly, I highlighted correspondences between the genes and pathways favored
by the Arctic Ocean microbiomes and the composition and transformations of dissolved
organic matter. Specifically, I found an enrichment in transformations involving sugars moieties
in the photic zone and a strong aromaticity signature in the dissolved organic matter
of the fluorescent dissolved organic matter maximum. These results show that the distinct
metabolism of the Arctic Ocean microbiomes imprint the composition of the dissolved organic
matter, uniquely influencing the Arctic Ocean biogeochemical cycles.
This thesis represents the first work to explore the metabolism of the Arctic Ocean microbiomes
in such a comprehensive fashion. Not only does this thesis systematically uncover a
multitude of metabolic processes of importance for the Arctic Ocean microbiomes, but it also
brings new discoveries on their biogeography, ecological context, and phylogenetic diversity
across prokaryotes and picoeukaryotes. Moreover, this thesis highlights the importance of these
processes by linking them to the composition and transformation of dissolved organic matter,
and hence biogeochemical cycles. As such, this thesis will serve as a base to guide experimental
and field work that will quantify the role of microbiomes in the biogeochemical cycles of the
Arctic Ocean. This will have important implications to understand and quantify how climate
change perturbs Arctic Ocean ecosystems
Proactive Security Policy Enforcement for Containers
Get PDFBy providing lightweight and portable support for cloud native applications, container environments have recently gained significant momentum. A container orchestrator, such as Kubernetes, can enable the automatic deployment and maintenance of a large number of containerized applications. However, due to its critical role, a container orchestrator also attracts a wide range of security threats exploiting misconfigurations or implementation flaws. Moreover, enforcing security policies at runtime against such security threats becomes far more challenging, as the large scale of container environments implies high complexity, while the high dynamicity demands a short response time. In this thesis, we tackle this key security challenge to container environments through a novel proactive approach. Our proposed approach leverages learning-based prediction to conduct the computationally intensive steps (e.g., security verification) in advance, while keeping the runtime steps (e.g., policy enforcement) lightweight. Consequently, this approach can ensure a practical response time (e.g., less than 10 ms in contrast to 600 ms with one of the most popular existing approaches) for large container environments (e.g., up to 800 Pods). We demonstrate its deployability by integrating our solution with Kubernetes, one of the most popular container orchestrators
Whether Bitcoin Has Same Properties as Gold in The Aspect of Hedging and Safe Haven against Stock Markets
Get PDFHaving a place of haven or a hedge against potential losses is an important feature of any investment strategy, but this is especially true during times of turmoil in the market. Bitcoin has demonstrated that it has the potential to become a new safe haven or hedging asset due to the fact that its value soared between 2010 and 2013 (during the Euro debt crisis and the banking crisis in Cyprus), and Bitcoin shares certain parallels with gold. In this study, we used the regression model developed by Baur and Lucey (2010) to investigate whether Bitcoin possesses the same hedging and safe-haven properties as gold against stock markets in the United States, the United Kingdom, China, Japan, and developed markets (world index) when extreme market conditions are present. The primary finding from the entire time from 2011-2022 implies that Bitcoin does not demonstrate hedge and safe haven properties like gold does, even though the safe haven property of gold is vanishing. Bitcoin, in particular, does not exhibit any of the characteristics of a safe haven in any of the markets in the study, and it only has hedge characteristics in Japan’s stock market. A further implication of our research is that the properties of a hedge and a safe haven of Bitcoin may change over time. According to the findings of the subperiod, Bitcoin served as a hedge and safe haven against all markets during the cryptocurrency cycle from its beginning to its peak. In addition, when Bitcoin gets more maturity, the hedging property might disappear, while the safe-haven property may become visible in most markets. Despite the fact that Bitcoin might have aspects of a hedge and a safe haven, the findings imply that the link between bitcoin and the stock market is still fairly weak. If investors are considering utilizing Bitcoin as a hedging instrument or a safe haven, they should proceed with extreme caution
The Psychological and Neural Bases of Extinction Learning
Get PDFExtinction is a fundamental learning and memory process that enables humans and animals to survive in the face of shifting environmental conditions. The context-specific nature of extinction learning is demonstrated by the renewal phenomenon, in which responding returns
following a change in context after extinction. Pavlovian fear conditioning procedures have primarily been used to investigate the psychological and neural processes mediating extinction. However, compared to passive defensive strategies, the mechanisms governing the extinction of
active defensive strategies are not well understood. This thesis examined the psychological processes mediating the extinction of both active and passive defensive responses using the shock-probe defensive burying task. We found robust ABA renewal and less marked ABC and
AAB renewal of passive coping behaviours. Active coping strategies linked to conditioned defensive burying did not display renewal, indicating that passive coping strategies are more prone to renewal than active coping strategies.These findings have important implications for
understanding how context influences the extinction of different defensive responses to aversive stimuli. Moreover, this thesis employed an appetitive Pavlovian conditioning procedure to investigate the neural mechanisms mediating the extinction of responding to a discrete sucrose
cue. Using Fos immunohistochemistry and correlational network analysis, we identified the neural correlates and networks associated with the recall vs extinction of responding to a sucrose-predictive Pavlovian cue. Our findings are consistent with those obtained using Pavlovian fear and operant reward-seeking procedures, which have demonstrated a functional dichotomy between the prelimbic (PL) and the infralimbic (IL) cortices of the medial prefrontal cortex. Namely, our results were consistent with the idea that the PL promotes the expression,
while the IL mediates the extinction of conditioned responding. Additionally, we found that the paraventricular nucleus of the thalamus (PVT) plays a role in the recall of appetitive Pavlovian responding, and a neural network including the IL and PVT is active during extinction but not
recall, suggesting that IL projections to the PVT may be involved in appetitive Pavlovian extinction. In support of this hypothesis, additional experiments found that optical stimulation of the IL-to-PVT pathway completely blocked appetitive Pavlovian renewal, while stimulation of
the PL-to-PVT pathway had only modest effects on renewal. In the same experiments, stimulation of the IL-to-PVT, but not the PL-to-PVT, pathway supported self-stimulation, suggesting that this pathway has a reinforcing property. Together, these findings provide novel insights into the neural mechanisms underlying the extinction of responding to appetitive
Pavlovian cues, and they point to the PVT as a critical node in the neural circuitry underlying the extinction of appetitive Pavlovian conditioned responding
Design of a synthetic data generation and simulation framework for mobility on demand applications
Get PDFUrbanization increases issues such as traffic congestion, lack of parking spots, and underutilized vehicles. In recent years, mobility-on-demand (MOD) concept has been proposed to effectively mitigate these issues. However, a common issue with MOD research is the lack of precise traffic data for conducting transportation-related studies and improving the proficiency of MOD systems. This is mainly because of data privacy concerns, GPS device limitations or errors, and expensive infrastructures for collecting real-time traffic data. Given the constraints, traffic simulations could be a reasonable solution for simulating the dynamic MOD activities such as distributing vehicles in the cities of interest and mimicking their movement behaviours. Despite the features that existing traffic simulators provide, they are not designed to support MOD use cases explicitly. For instance, background traffic generated by these simulators mostly follows random algorithms and the traffic flow is not based on real traffic patterns of the region. Another issue could be the lack of integration APIs to accept user inputs while the simulation is running to adapt the behaviour of the simulation. In this thesis, a synthetic MOD data generation framework is proposed. This framework takes a map region, real traffic data, and service vehicles trip plan as input. Using the ARIMA machine learning algorithm, we could predict demand and generate background traffic, followed by simulating the service vehicles in the region. The proposed framework generates synthetic traffic based on real traffic patterns and then simulates the service vehicles' movements on the map. While the simulation is running, the framework monitors the vehicles and collects real-time trajectory data. This framework leverages the features of SUMO as a microscopic simulation engine. In addition, established HTTP APIs enable third-party integration and allow users to control vehicles and trips on the map before and during the simulation execution. The offered simulation features include and are not limited to, the importation of a trip plan for numerous vehicles and the update of vehicle destinations. In addition to integration APIs, the proposed framework provides a graphical user interface to facilitate simulation setup and execution. The provided user interface enables users to explore a map, specify a region on the map, and then choose it as a simulation boundary. Throughout the simulation, the software core captures and stores real-time data on vehicle movement in a database that might be utilized for mobility-on-demand research. This simulation framework returns comprehensive service vehicle trajectories, departure time, destination time, travel duration, route length, and service vehicle status. The proposed software is open-source and publicly available, and its capabilities could be improved for future study
Un modèle d’enseignement collaboratif axé sur la pratique éco-art en éducation artistique au secondaire
Get PDFRÉSUMÉ
Cette recherche a pour but de développer un modèle d’enseignement collaboratif axé sur la pratique éco-art qui relie l’éducation artistique et l’éducation relative à l’environnement au secondaire. Celle-ci examine les avantages d’un enseignement animé par une équipe d’experts composée d’un enseignant spécialisé en arts plastiques et d’un artiste professionnel du programme La culture à l’école. Plus précisément, cette recherche s’appuie sur l’expérience et l’expertise de trois équipes formées d’un enseignant et d’un artiste pour créer un projet éco-art en milieu scolaire par des approches collaboratives. Suivant les cinq phases de modélisation, ces équipes ont travaillé à la préparation, planification, réalisation, évaluation et communication de trois projets éco-art auprès de six classes d’élèves dans deux écoles durant l’année scolaire 2018-2019.
Selon une méthodologie qualitative interprétative, cette étude s’oriente sur les principes de la recherche-action collaborative. Par un cycle d’actions dynamiques, elle contextualise la communauté d’apprentissage comme une stratégie pédagogique de cocréation pour apporter des améliorations à la pratique personnelle, la formation professionnelle et la qualité du milieu de vie. Son cadre théorique issu du socioconstructivisme, de la démarche de projet et du nouveau matérialisme ont permis d’établir des niveaux d’interrelation pouvant mener à terme un véritable processus de partenariat. Celui-ci a également favorisé un rapport plus étroit avec l’environnement par la construction d’une identité commune faisant appel à la réflexion et aux dimensions éthiques dans la production d’œuvres éco-art avec la participation des élèves.
Les résultats provenant d’entrevues semi-dirigées, d’observations directes, de groupes de discussion et de journaux de bord démontrent que la complémentarité du rôle de l’enseignant et de l’artiste contribue à enrichir la pratique par le partage de savoirs, savoir-faire et savoir-être dans une perspective de durabilité. L’atteinte de ces objectifs laisse entrevoir de nouvelles formes d’expression artistique plus responsable qui se rattachent aux préoccupations du milieu de pratique en art contemporain. Le modèle d’enseignement proposé se situe entre les savoirs savants du curriculum formel et les savoirs d’expérience du curriculum réel. Se référant au chaînon de la transposition didactique, l’auteur offre un guide à la fois pratique et théorique basé sur des méthodes autobiographiques d’investigation pouvant se combiner au domaine de la pédagogie, de l’écologie de l’éducation artistique et des arts visuels.
ABSTRACT
This research aims to develop a collaborative teaching model focused on eco-art, a practice that connects arts education and environmental education in secondary school. It examines the advantages of a teaching method led by a team of experts: a teacher specializing in the visual arts, and a professional artist from the Culture in the Schools program. More specifically, this research is based on the experience and expertise of three teams made up of the aforementioned professionals when creating an eco-art project in the school environment through collaborative approaches. Following the five modeling phases, these teams worked on the preparation, planning, implementation, evaluation, and communication of three eco-art projects with six classes of students in two schools during the 2018-2019 school year.
Using an interpretative qualitative methodology, this study is based on the principles of collaborative action research. Through a cycle of dynamic actions, it contextualizes the learning community as an educational co-creation strategy to bring about improvements in personal practice, professional training, and the quality of the living environment. Its theoretical framework, derived from socio-constructivism, the project approach, and the new materialism, has made it possible to establish levels of interrelation that can ultimately lead to a true partnership process. It also fosters a closer relationship with the environment through the construction of a common identity calling for reflection and ethical dimensions in the production of eco-art works with the participation of students.
The results, obtained from semi-directed interviews, direct observations, focus groups, and journals, show that the complementarity of the role of the teacher and the artist contributes to enriching practice by sharing knowledge, know-how, and interpersonal skills from a sustainability perspective. Achieving these objectives suggests new forms of more responsible artistic expression that relate to the concerns of the contemporary art practice community. The proposed teaching model is situated between the scholarly knowledge of the formal curriculum and the experiential knowledge of the real curriculum as implemented in reality. Referring to the chain of didactic transposition, the author offers a practical and theoretical guide based on autobiographical methods of investigation, that can be combined with the fields of pedagogy, ecology of artistic education, and the visual arts