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The great moving countering violent extremism show: An ethnography of CVE in the Canadian context
Get PDFMy dissertation critically examines through ethnographic fieldwork the rise of countering violent extremism [CVE] programs in Canada. CVE is an offshoot of counter-terrorism, with programs first taking hold in the mid-2000s following ‘homegrown terrorism’ incidents in Madrid and London. CVE is based on the premise that a ‘radicalization process’ precedes terrorism. This allows for security and civil society-based interventions in the ‘pre-crime’ space to interrupt terrorism before it happens. The most thorough and controversial example of this is the UK’s Prevent strategy, which legally mandates human services professionals to refer individuals showing signs of ‘radicalization’. In Canada, no such duty exists, though its national strategy nonetheless aims to harness ‘all of society’ toward preventing violent extremism, enlisting the cooperation of teachers, artists, psychologists, social workers along with actors in the private sector.
My study is not about how individuals turn to ‘violent extremism’ or ‘radicalization’ but rather about examining that edifices that have created to respond to these perceived problems The implications of CVE as an ‘all of society’ endeavour are manifold, particularly as the scope of CVE expands beyond ‘Islamism’ toward preventing ‘all types’ of violent extremism, most recently on right-wing groups and violence against racial, ethnic, and gender minorities. Broadly, my research attempts to conceive of the implications of this expansion. What drives CVE’s growth in the face of sustained criticism over its deleterious impacts on Muslim communities? How do practitioners in CVE align their interests with the cause? What social functions does CVE take on? Moreover, can boundaries even be drawn around what constitutes CVE?
My study draws on interviews with 46 CVE practitioners and participant observation over a three-year period (2018-2020) with CVE entities operating in Canada. My findings indicate how an absence of knowledge over how to conduct CVE propels its encroachment into ever more diverse areas of social life. The paradigm operationalizes ‘uncertainty’ to enroll actors with diverse interests and foster partnerships with communities including those (racialized, Indigenous, LGBTQ) that have had fraught relationships with security institutions.
In Chapter 1 - Searching for the CVE space I discuss my immersion in CVE and the type of fieldwork activities conducted. I also attempt to define my research object, outlining how CVE comprises a field of practice, a paradigm, a moral-social imperative, and lastly a space. Chapters 2 and 3 historicize CVE’s contemporary presence and disturb common understandings of its origins. I critique the explanation of CVE’s rise as a necessary and spontaneous reaction to evolving security threats to understand it as an outcome of performative security knowledge, where new security threats are discursively created rather than responded to. Chapters 4 and 5 focus on my fieldwork experience, examining how actors ‘enroll’ in the CVE cause through the open-ended, speculative quality of its activities. A distinction emerged with Muslim-identifying CVE practitioners, whose motivations to represent their communities in often hostile institutions and reduce the harm of CVE practices were typified by the repeated phrase “if you’re not at the table, you’re on the menu”. In the conclusion chapter I connect the varying threads of preceding analysis and what they portend for CVE’s effects on societies. This includes examining how CVE’s efforts to redirect political grievances toward ‘pro-social’ ends potentially disempowers social justice movements, reinforcing state hegemony and existing power inequities
An XAI-based Framework for Software Vulnerability Contributing Factors Assessment
Get PDFSoftware vulnerability detection plays a proactive role in reducing risks to software security and reliability. Despite advancements in deep learning-based detection, a semantic gap persists between model-learned features and human-interpretable vulnerability semantics. The challenge lies in the absence of a systematic approach to assess feature importance, capable of explaining the relationship between these two elements. Explainable Artificial Intelligence (XAI) techniques become indispensable in offering comprehensive explanations of features learned by AI models, emphasizing their applicability in software vulnerability detection.
This research introduces an XAI-based framework to systematically evaluate XAI techniques and apply them for assessing the contributing factors of feature representations in classifying soft- ware code into Common Weakness Enumeration (CWE) types. The focus is on applying XAI methods to examine the importance of features underlying vulnerability detection. An additional challenge arises from the lack of a systematic evaluation to ensure consistent explanation results during the selection of state-of-the-art XAI methods.
To address this, this thesis defines three evaluation metrics for XAI: consistency, stability, and efficiency. A novel XAI method, named Mean-Centroid PredDiff, is introduced to strike a balance among these three metrics, significantly enhancing the framework’s efficacy. This method, along with SHAP, are integrated into the framework based on their well-performance across the evaluation in three domain case studies.
Findings from this work reveal that the proposed framework enables the summarization of the importance of 40 syntactic constructs and the similarities among 20 CWEs based on graph- embedded semantic features. The study results align closely with expert knowledge from the CWE community, achieving approximately 77.8% Top1, 89% Top5 similarity hit rates and mean average precision of 0.70 in CWE classification. The study validates the significance of attention values of transformer-based models in representing the importance of code tokens.
Overall, this thesis contributes a new XAI method to the open-source community, achieving a trade-off of efficiency with consistency and stability. In addition, the XAI-based framework success- fully assesses the nine meta syntactic constructs importance across 20 CWE types and evaluate their similarity. The dataset and the code of framework have been made publicly available on GitHub
Generation and storage of gas from waste decomposition in municipal solid waste landfills
Get PDFThis Ph.D. thesis focuses on optimizing municipal solid waste flows and modeling and managing landfill gas generation from organic wastes. First, it presents a statistical survey of waste flow in New York and Montreal and a calculation of the energy recovery potential of food and yard waste in these cities. The results indicate a low diversion rate from landfills, with significant biogas generation potential from these wastes, contributing to around 2.5% of the energy supply in these cities. Second, it evaluates the current and proposed waste management systems in Montreal, applies a life cycle assessment using the IWM-2 software, and optimizes waste flows using a genetic algorithm to decrease energy consumption, greenhouse gas emissions and costs. The optimized waste flow considers 58% landfilling and shows the importance of further research on landfills.
The following chapters study the generation and storage of gas from waste decomposition in municipal solid waste landfills in the province of Quebec, Canada. The fifth chapter addresses the modeling scenarios of landfill gas generation based on a modified first-order decay model. It uses a genetic algorithm to independently fit parameters to methane and hydrogen sulfide generation models. The results show that differentiating more waste types improves the modeling accuracy, and the changes in waste management strategies within a landfill’s decade-long lifetime require various modelling assumptions. Also, the work reveals the importance of considering how different landfill sectors are filled over time. The sixth chapter explores the potential of utilizing stored methane in landfills as an energy source. The study investigates the gas collection system shutdown and restart periods, determining the duration required to maximize collected stored methane. The results show that it takes 0.6 hours to start methane collection and 2.5 hours to reach the maximum collected stored methane. Additionally, the collected stored methane represents 10.5% of landfill gas flow
Cybersecurity Events, Financial Analysts, and Earnings Forecast Uncertainty
Get PDFThis dissertation examines the role of financial analysts in evaluating cybersecurity events within the commercial banking industry. The focus on commercial banks arises from their visibility and attractiveness as cyber attack targets. The increasing number of such incidents in recent years has garnered significant public scrutiny, especially from investors and analysts. The situation engenders a sense of ambiguity regarding the outlook of the affected business.
The dissertation comprises two complementary empirical chapters. Chapter 2 presents an exploratory case study on financial analysts’ interactions with management in the context of conference calls following cyber incidents. Such interaction provides insights into the kind of information that financial analysts seek from management, and which presumably enters analysts’ decision-making process when forecasting a bank’s financial situation. The case study reveals that financial analysts ask more questions about cyber-related issues such as digital fraud, cloud technology, and technological investments to encourage top management at some banks to discuss their prevention efforts concerning cybersecurity risks and controls. When asked directly, managers discuss cyber incidents upfront.
Chapter 3 examines how cybersecurity incidents at commercial banks affect analyst forecast properties. Cyber incidents affect financial analysts’ information environment on two dimensions: uncertainty and information asymmetry. After security breaches, information asymmetry increases due to management’s standard practice of securing cybersecurity data to mitigate potential negative financial consequences. Despite the high information asymmetry underlying their earnings forecasts, analysts seek to improve the information environment's quality and reduce uncertainty in the financial market.
Financial analysts who change their earnings forecasts in reaction to cyber attacks do not necessarily do better than those who did not revise their forecasts. Prior studies show that low information asymmetry reduces forecasting risks and drives financial analysts to revise earnings forecasts regularly. Since cyber information is scarce, financial analysts are reluctant to change their earnings estimates when information asymmetry is high. In addition, analysts exhibit different forecasting behaviors depending upon the type of cyber event (involving confidentiality, integrity or availability issues).
This thesis provides new insight into the information dynamics around cybersecurity by concentrating on a significant market intermediary. The thesis contributes to the literature on financial analysts by highlighting their demand for information related to cybersecurity issues and reactions to cybersecurity events. Thus, this thesis advances our understanding of the inputs analysts use in decision-making and how they respond to events that exacerbate uncertainty and information asymmetry in the information environment. Regulators could use these findings to orient their policies regarding mandatory disclosure requirements or guidance on cybersecurity issues. Managers can learn about what cybersecurity-related disclosures capital markets require
Modelling And Design Optimization of Compound Thick-Walled Cylinders Treated with Autofrettage, Shrink-Fit, And Wire-Winding Processes
Get PDFThick-walled cylinders are crucial in various industrial applications, including mechanical, aerospace, naval, offshore, petrochemical, military, and electronics industries. These cylinders function as pressure vessels in diverse structures under different loading conditions. Some applications, such as steam boilers and aerospace propulsion systems, encounter severe cyclic thermo-mechanical loading conditions. Modeling the impact of these cyclic conditions is challenging due to the limited time between successive loads, preventing adequate cooling and resulting in thermal accumulation within the cylinder material. Thus, stress and temperature distributions within the cylinder thickness are altered, affecting mechanical and thermal properties. Existing models commonly assume temperature-independent material properties, utilizing the uncoupled thermo-elasticity approach. However, it is essential to adopt temperature-dependent material properties and a coupled thermo-elasticity approach for a precise estimation of residual temperature and stress distributions throughout the cylinder wall, significantly influencing thick-walled cylinder design.
Moreover, under severe loading conditions, simple virgin cylinders may fail to sustain applied loads without undesirable increases in thickness and weight. Consequently, various surface treatment manufacturing processes, such as shrink-fitting, wire-winding, and autofrettage, have been developed to enhance durability and load-bearing capacity. These processes induce beneficial compressive stresses near the bore region, countering tensile stresses that would normally develop during loading, thus improving their fatigue lifetime. Accurate prediction of residual stresses resulting from these processes is pivotal for optimal cylinder design. However, due to several limitations associated with each individual reinforcement process, different combinations of reinforcement processes are proposed to alleviate these limitations. Estimating residual stresses due to such combinations is complicated, leading many studies to avoid analytical models.
In response to these challenges, this thesis explores the behavior of temperature-dependent thick-walled cylinders treated with various reinforcement processes under cyclic thermomechanical loads. The classical coupled thermo-elasticity approach estimates thermal and mechanical responses, highlighting the significance of considering temperature-dependent material properties. Furthermore, an efficient analytical method is developed for estimating the residual stress profiles in cylinders with diverse reinforcement processes. This method forms the basis for a machine learning-based design optimization, streamlining the process and reducing computational costs significantly. Fatigue life assessment of the optimal configuration underscores the improvement achieved
Trolling Behaviors and Victimization in Online Brand Communities
No full textThe growth in online technology and social media use has led to a significant boom in online communication and participation. The current literature on online interactions has mainly focused on how online platforms encourage positive forms of engagement, but it is important to recognize that these platforms also create opportunities for negative types of engagement such as trolling to occur, which has become increasingly prevalent online. Currently, there is a growing academic interest in online trolling behaviors. However, the current research on trolling has some crucial limitations that must be addressed. Firstly, the trolling construct lacks conceptual clarity and trolling literature has been rather limited in scope, especially in the marketing context. To address this issue, Essay I conceptually explored how trolling can emerge in the brand community context. More specifically, this research introduced the brand trolling concept and developed numerous research propositions and questions that are foundational to the novel concept on the individual-, community-, and brand/organization-level. The service-dominant logic was used as a theoretical framework to illustrate the highly contextual and expansive nature of brand trolling in the brand community environment. Overall, this essay developed a more solid foundation for the trolling construct and it introduced a novel perspective on how the empirical relationships and conceptual elements of trolling can be expanded to the marketing domain on multiple levels.
Another issue prevalent in trolling literature is how its conceptualization has not been fully agreed upon by scholars and practitioners alike. Accordingly, Essay II addressed this issue by developing valid and reliable scales for trolling behavior and trolling victimization. Appropriate scale development procedures such as exploratory and confirmatory factor analyses, reliability tests, and numerous validity tests were conducted throughout multiple studies. The results of the studies demonstrated how trolling behavior and trolling victimization are both reliable, valid and multidimensional constructs. This research further solidifies the foundation for trolling behavior and victimization that should help scholars research the concepts more appropriately in the future
Automatic Evaluation of Collaterals in Ischemic Stroke
Get PDFIschemic stroke, caused by blocked arteries in the brain, is one of the leading causes
of death and disability worldwide. Endovascular thrombectomy treatment (EVT) is one
of the best treatment strategies for restoring blood flow through blocked arteries, but its
success rate depends on a number of factors, including the extent of a patient’s collateral
circulation. Collateral circulation is a subsidiary vascular network that gets activated when
the main conduits fail due to ischemic stroke. It helps viable brain tissues to get oxygen
and nutrients temporarily.
Evaluation of collaterals by visual inspection of radiologists is time-consuming and
prone to inter and intra-rater variability. Thus, computer-aided systems can provide more
consistent and reliable assessments of collaterals. Four-dimensional computed tomography
angiography (4D CTA) is a reliable method for detailed cerebral vasculature imaging,
preventing inaccurate collateral estimation compared to single-phase CTA. Alongside 4D
CTA, readily available non-contrast computed tomography (NCCT) serves as a frontline
diagnostic tool, free from contrast agents’ potential adverse effects. Hence, we propose
computer-aided systems for automatic collateral evaluation in ischemic stroke using 4D
CTA and NCCT imaging.
We propose an automatic quantification method considering low-rank decomposition,
a classic machine learning (ML) method as well as deep learning (DL) methods for
the automatic evaluation of collaterals. DL models, while capable of automatic feature
extraction unlike classic ML models, face challenges due to limited ischemic stroke data. To
overcome data scarcity and class imbalance, we employ transfer learning with focal loss and
Siamese network. Furthermore, for efficient 3D vasculature segmentation without extensive
slice annotation, we introduce few-shot learning for cerebral blood vessel segmentation which
can be a preprocessing step to collateral evaluation
Occurrence and transport of pollutants from spilled oil and microplastics in the coastal areas
Get PDFThe coast is a complex environment that comprises seawater, underwater, soil, atmosphere, and other environmental factors. Traditional and new pollutants, represented by oil spills and microplastic (MPs), persist in posing a constant threat to the ecosystems and social-economic features of coastal regions. Besides, the shoreline is exposed to various environment conditions, which may significantly affect the behaviors of pollutants on beaches. An in-depth understanding of the occurrence and fate of pollutants in coastal areas is a prerequisite for the development of sound prevention and remediation strategies. Firstly, the physicochemical behavior of crude oil on various types of shorelines under different environmental conditions were reviewed. The penetration, remobilization, and retention of stranded oil on shorelines are affected by the beach topography and the natural environment. The attenuation and fate of oil on shorelines from laboratory and field experiments were discussed. In addition, the source, type, distribution, and factors of MPs in the coastal areas were summarized. What is more, the occurrence and environmental risk of emerging plastics waste—personal protective equipment (PPE)—in the coastal environment during and pandemic were discussed.
Then, the role of natural nanobubbles (NBs) in the fate and transport of spilled oil were investigated through laboratory experiments and model simulations. NBs significantly increased the concentration of dissolved oxygen as well as changed the pH, zeta potential, and surface tension of the water. With the assistance of external energy, the bulk NBs enhanced the efficiency in oil detachment from the surface of the substrate. At the same time, the surface NBs on the substrate obstructed the downward transport of oil colloids. Considering the behavior between the NBs in two different phases and the oil droplets, the oil droplets tended to bind to the NBs.
Next, the behavior and movement of various MPs in the presence of bulk NBs was explored. In the presence of NBs, the binding of MPs and NBs resulted in an increase in the measured average particle size and concentration. The velocity of motion of MPs driven by NBs varies under different salinity conditions. The increase in ionic strength reduced the energy barrier between particles and promoted their aggregation. Thus, the binding of NBs and MPs became more stable, which in turn affected the movement of MPs in the water. Polyethylene (PE1) with small particle size was mainly affected by Brownian motion and its rising was limited, therefore polyethylene (PE2) with large particle size rose faster than PE1 in suspension, especially in the presence of NBs.
The effect of nanobubbles on the mobilization of MPs in shorelines subject to seawater infiltration was further studied. The motion of MPs under continuous and transient conditions, as well as the upward transport induced with flood were considered. Salinity altered the energy barriers between particles, which in turn affected the movement of MPs within the matrix. In addition, hydrophilic MPs were more likely to infiltrate within the substrate and had different movement patterns under both continuous and transient conditions. The motion of the MPs within the substrate varied with flow rate, and NBs limited the vertical movement of MPs in the tidal zone. It was also observed that NBs adsorbed readily onto substrates, altering the surface properties of substrates, particularly their ability to attach and detach from other substances.
Finally, the changing characteristics and environmental behaviors of PPE wastes when exposed to the shoreline environment were examined. The transformation of chain structure and chemical composition of masks and gloves as well as the decreased mechanical strength after UV weathering were observed. In addition, the physical abrasion caused by sand further exacerbated the release of MPs and leachable hazardous contaminates from masks and gloves.
In conclusion, the coastal zone is threatened by various pollutants, including traditional pollutants (like the oil spill) and emerging pollutants (like MPs). Due to the complexity of the coastal zone, the occurrence, transport and fate of pollutants can be controlled by many factors, and some factors that are ignored before can also alter the environmental behavior of pollutants in the coastal zone. Natural NBs can change the properties of the water environment and affect the surface properties of the substrate. Bulk NBs contribute to the oil detachment from the sand surface, and surface nanobubbles in the substrate obstruct the downward transport of oil colloids. The behavior and mobilization of MPs in the coastal `zone are subject to mutual forces between the substrate, MPs, NBs, and other factors. Coastal zones are not only the main receptor of pollutants from oceans and lands but also play a key role in their fate and transport
Development, Characterization and Performance Assessment of High Entropy Coatings (HECs) Deposited Through Various Thermal Spray Methods
No full textSurface engineering is of utmost importance in ensuring the efficient and long-lasting performance of components across diverse industries, such as automotive, aerospace, mining, transportation, and biomedical applications. Conventional Ni-based alloys (e.g., Mar-M-247, PWA1484 and PW1480) commonly utilized in these sectors often face limitations and failures under harsh operating conditions, attributed to factors like friction, wear, oxidation, and corrosion. To address these challenges, this Ph.D. dissertation investigates the potential of high entropy alloys (HEAs) as a viable solution for enhancing tribological performance under extreme conditions. HEAs are unique alloys with five or more principal elements in near-equal atomic percentages, offering exceptional mechanical and thermal properties.
The study investigates four HEA systems: CrMnFeCoNi, Al0.5FeCrMnCoNi, AlFeCrMnCoNi, and AlCoCrFeMo, particularly for their use as coatings. The research involves producing HEAs using solid-state reactions and utilizing various thermal spray techniques such as low-pressure cold spraying (LPCS), flame spraying (FS) and high velocity oxygen fuel (HVOF) for coating deposition. The study meticulously investigates how the deposition process and various spraying parameters influence coating composition and microstructure. Additionally, a transverse scratch test is employed to evaluate the cohesion and adhesion of the coatings. Comprehensive characterization techniques, such as high-resolution scanning electron microscopy (SEM), electron channeling contrast imaging (ECCI), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), Raman analysis, and Electron Backscatter Diffraction (EBSD), are employed to evaluate the microstructure.
Results show the formation of solid solution phases in coatings with minor oxide formation. CrMnFeCoNi coatings exhibit a single solid solution with a face-centered cubic (FCC) structure, while AlFeCrMnCoNi coatings consist of a combination of body-centered cubic (BCC) and minor FCC phases. AlCoCrFeMo HEA coatings exhibit a BCC/B2 phase structure. LPCS coatings, in particular, stand out for not exhibiting oxide formation and retaining the feedstock phases. When Al was added to the CrMnFeCoNi HEA system, it resulted in increased hardness but reduced cohesive strength in the AlFeCrMnCoNi coatings.
All thermally sprayed high entropy coatings (HECs) were tested on a ball-on-disc tribometer under dry sliding reciprocating conditions up to 350°C, using alumina counterballs. The tribological testing revealed that the HVOF-sprayed AlCoCrFeMo coatings outperformed all other tested HECs across all temperature conditions. This superior wear resistance can be attributed to several key factors, including the presence of finer splats, controlled oxide formation within the coating, higher hardness due to the influence of the BCC phase, and the development of a protective Co-based oxide film at the contact region.
Overall, this Ph.D. dissertation has proposed innovative design strategies to enhance the wear resistance of high entropy coatings (HECs) and has identified critical parameters affecting wear performance. The research significantly contributes to materials design by elucidating the relationship between interfacial processes and tribological behavior. It establishes a strong foundation for the future development of HEA-based coatings, emphasizing their potential as next-generation tribological interfaces for demanding operating conditions
Dynamics of Hybrid-Actuated Soft Robots with Stiffness Adaptation for Robot-Assisted Interventions
Get PDFThe lack of adaptability in surgical instruments has limited the widespread adoption of robot-assisted interventions. The objective of this doctoral research was to address the inherent trade-off between the deformability and force transmission capacity of minimally invasive surgery (MIS) instruments. Current instruments, such as catheters, tend to exhibit either excessive flexibility, rendering them unsuitable for load-bearing tasks, or excessive stiffness, limiting maneuverability in anatomical regions with complex geometry. The hypothesis underlying this research proposed that by controlling the stiffness of a soft robot, which serves as an MIS instrument, it is possible to increase its deformability during the steering phase while increasing stiffness during load-bearing tasks to ensure effective force transmission. The approach put forth in this study utilized a hybrid air-tendon actuation system, which has not yet been explored in existing literature for stiffness adaptation. To justify this hypothesis, a continuum mechanics model based on the nonlinear Cosserat rod method, incorporating hyperelastic material properties and accommodating large deformation kinematics, was developed and experimentally validated. This model demonstrated the feasibility of stiffness control through hybrid actuation. Initially, a static Cosserat rod model was developed and validated in a 2D context. Furthermore, the model was refined to incorporate the hyperelastic properties of the soft material, and its validity was established in 3D scenarios. Next, a dynamic model for the Cosserat rod was developed and validated using experimental data. Lastly, a parametric finite element method was used to optimize the geometry of the soft robot based on a defined goal function to reduce unnecessary radial expansion during inflation and enhance axial force transmission