Liste complète
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2019 — Asymptotic Analysis of Method of Moments Extimators of Paramaeters p and m For The Binomial DistributionRésumé
The aim of the thesis is to study asymptotic properties of estimators for the Binomial distribution by the Method of Moments and an application of these estimators to evaluate characteristics of the neuromuscular junction (synapse). To achieve these goals it is necessary to solve the following problems: i. Derivation of estimates of parameters of Binomial distribution by the Method of Moments; ii. Derivation of the parameters of the asymptotic normality by the Delta-method; iii. Comparison of the derived asymptotic with the true probabilistic characteristics of the estimators by the method of statistical simulations; iv. Estimation of parameters m and p … Lire la suite
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2016 — A Novel Approach for Simulating Soil and Pipe Response to Seasonal, Environmental and Field ConditionsRésumé
Climate change related problems are increasing in occurence and severity leading to significant econocmic losses in many places of the world. In semi-arid environments, like Saskatchewan, the main phenomenon involved in pipe breakages is the volume change behavior of unsaturated clay deposits. Underground pipelines are typically buried within the upper zone of soil deposits, and therefore, are highly affected by soil nature and the different environmental conditions present on the ground surface. To accurately model field conditions, a mathematical formulation of native soil conditions was developed based on a bimodal soil water characteristic curve (SWCC) and other constitutive relationships. In … Lire la suite
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2017 — Coyote Stories: Attending to Narratives as Life-MakingRésumé
Living, telling, reliving and retelling my own autobiographical stories of experience, along with the stories of experience of students from my early years as a teacher, I entered formal narrative inquiry with two co-participants, Isabel and Anne-Marie. My personal and social justifications for this research were rooted in my living and living out silenced stories inside and outside of educational landscapes. In the midst of the inquiry journey, my research puzzle shifted, changed, and emerged: How might I live alongside students, attending narratively to our stories of experience, particularly to silenced stories, and then how might our identity making stories, … Lire la suite
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2024 — Influence of pore structure and fluid properties on the dynamics of foamy oil production: an experimental and numerical analysisRésumé
Cyclic Solvent Injection (CSI) stands out as one of the leading solvent-based post-CHOPS Enhanced Heavy Oil Recovery (EHOR) methods, celebrated for its energy efficiency, improved oil quality, and environmental benefits. Given the escalating concern over greenhouse gas emissions, exploring the use of CO2 in EHOR methods is crucial for mitigating the greenhouse effect. Studies have demonstrated that mixing CO2 with other solvents can enhance CSI performance by leveraging foamy oil flow as the primary driving force. Our state-of-the-art microfluidic systems, developed in-house, offer precise visualizations of the process, and enable controlled simulation of reservoir properties throughout experimental series. In this … Lire la suite
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2011 — Advanced Music Training and Executive Function: A Neurocognitive StudyRésumé
The objective of this study was to assess the relationship between advanced music training and neurocognitive functioning, with specific focus on executive function, working memory, and tactile interhemispheric transfer. Twenty professional musicians and a comparison group of 19 individuals with no formal music training or performance experience completed a battery of measures of executive functioning, working memory, and interhemispheric transfer. The musician group had an average of 20.4 years (SD = 9.6) of formal music training and had started formal music training at a mean age of 5.8 years (SD = 2.5). Results revealed significantly better performance of the musicians … Lire la suite
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2013 — Catalysts for Hydrogen Production by the Auto-Thermal Reforming of GlycerolRésumé
Due to a number of major environmental issues, essentially greenhouse gas emissions and fossil fuel reliance, the implications of hydrogen as a promising clean energy carrier have significantly increased. In this respect, the use of bio-renewable feedstock such as glycerol for hydrogen production is becoming important. The majority of natural glycerol is produced as a by-product of the bio-diesel industry. Presently, almost all crude glycerol is refined before its ultimate end use. It is the ultimate goal of the present study to develop an effective catalytic auto-thermal reforming process to convert glycerol into top value bio-based products. Glycerol can be … Lire la suite
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2025 — The germ game design framework for user engagement, retention, and monetizationRésumé
Many video game development teams passionately pursue innovative concepts they believe will appeal to users, often resulting in well-crafted games as products. However, despite the creativity and effort of the teams, the resulting games frequently fail to realize their full audience potential and economic viability. This thesis presents the GERM framework to enhance user engagement, retention, and monetization in video games. The framework is named GERM, which is short for Game Engagement, Retention, and Monetization, to emphasize its focus on strengthening these three foundational areas. The framework elements are a Multi-Objective Goal Generator, Reward System, Timer Scheme, Social Dynamics, Enhancers, … Lire la suite
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2020 — Training Tomorrow's intelligence-Amplified Policy Analyst: A Public Administration Curriculum for the Digital EraRésumé
Technology change has continually affected the practice of public administration and policy analysis, and it is anticipated that an acceleration of this change will affect the required skill sets of public servants in the coming decade. This thesis focuses on two aspects of technology change as it might affect public policy analysis and the skill requirements of public servants: the transition from policy analysis to policy analytics; and the adoption of artificial intelligence (AI) by knowledge workers as a complement to (rather than substitute for) their activities, conceptualized as Intelligence Amplification (IA). Interviews were conducted with Canadian public sector executives … Lire la suite
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2024 — The development of an efficient model using deep learning for stray clays position prediction in the GPR data for potash mining operationsRésumé
This thesis focuses on the analysis of ground penetrating data obtained from potash mining room roofs with the goal of enhancing safety through the automatic detection of anomalies in the roofs. Ground Penetrating Radar (GPR) is a tool used to detect the position of geological layers of the earth. This is possible by transmitting an electromagnetic (EM) signal through an antenna and capturing the reflected signal representing the positions of the layers. Conventionally, a region of at least 60 centimeters from the roof to the 414 clay seam is necessary for mining operations. Therefore, detecting the position of the 414 … Lire la suite
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2023 — Discretization of nature-inspired techniques for combinatorial problemsRésumé
Scientists across various domains like scheduling, computational biology, and machine learning face constraint-solving and optimization problems. Classical systematic and mathematical methods often fall short of providing suitable solutions for such complex problems, leading to the introduction of metaheuristic algorithms. These algorithms exhibit diverse characteristics and can effectively address specific optimization problems. The primary motivation is to develop robust metaheuristics that can efficiently handle scaling problems. However, one challenge with metaheuristics is their immature convergence. In the context of Constraint Satisfaction Problems (CSPs), a framework applicable to numerous real-world problems, metaheuristics play a significant role. To address these objectives and challenges, … Lire la suite
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2014 — Mutex Pair Detection for Improving Abstraction-based HeuristicsRésumé
Problem solving is a very important aspect of arti cial intelligence. This thesis focuses on problems that can be formulated as search problems in a state space. Since blindly searching in a large state space is usually not enough for solving real world problems, it is required to equip the search algorithms with heuristics (estimates of the distance from any state to the goal) to guide the search. Further, the more accurate the heuristic function the more e cient the heuristic search algorithm will be. A popular way for creating domain-independent heuristic functions is by using abstraction, an abstract (coarse) … Lire la suite
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2024 — The Bures metric: from positive linear functionals to completely positive mapsRésumé
This thesis aims to explore the evolution of the notion of the Bures metric in Operator Algebras, from its introduction by D. Bures in 1969 for normal states of von Neumann algebras to its extension to completely positive maps of C∗-algebras by D. Kretschmann, D. Schlingemann, and R. Werner in 2008. While Bures’ work is rooted in von Neumann algebras, our primary focus will be on unital C∗-algebras. We will explore the definitions and main properties of the Bures metric for positive linear functionals, providing bounds and additional insights into fidelity — a measure closely related to the Bures metric. … Lire la suite
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2018 — Walking in a Good Way: A Self-Study of MÔNIYÂSKWÊWRésumé
This is a contributing work to the self-study world for non-Indigenous educators navigating the pathways of Indigenous Education. The uniqueness of this work is embodied in focusing on Indigenous teachings as a framework. In seeking miskâsowin, I used self-study as a methodology to inquire into the moments of tension I experienced as a non-Indigenous educator teaching Indigenous Studies. Through the (re)telling of stories of tension, I have come to new understandings of what it means to be môniyâskwêw in these spaces. Indigenous knowledge empowered my miskâsowin framework of analysis as I explored nêhiyawêwin teachings as a way of inquiring into … Lire la suite
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2023 — Credit card fraud detection using incremental feature learningRésumé
Detecting credit card fraud is essential and it is one of the most popular payment methods. Credit card fraud can cause huge losses for cardholders. Therefore, so many studies have focused on proposing different standard machine learning methods and limited use of incremental learning to create a robust detective system. None of these studies can solve all the credit card fraud challenges together. The reason is the complicated real-world scenario and data we have in our hands. Some of these challenges are rapid data arrival rate, concept drift which causes model performance to decline over time and data sensitivity which … Lire la suite
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2022 — Gamma-decay spectroscopy of sodium-26Résumé
In November 2017, an experiment was performed at the Isotope Separator and Accelerator (ISAC) facility at TRIUMF, whose goal was to perform a precise measurement of the beta decay half life of 14O. Beams of 26Na, which are readily available at ISAC, were also used during that experiment for performing rate-dependent calibrations and performance tests of the GRIFFIN spectrometer for detecting gamma rays. The decay of 26Na provides an ideal test case to verify the methodology of the data analysis and ensure that GRIFFIN can provide accurate results, with minimal losses, even at relatively high-counting rates. Given that a previous … Lire la suite
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2021 — The End of the Policy Analyst? Testing the Capability of Artificial Intelligence to Generate Plausible, Persuasive, and Useful Policy AnalysisRésumé
Public servants provide support for decision makers through synthesis documents such as briefing notes. To develop recommendations for dealing with the problem, they use a variety of sources for research and analysis. This current research seeks to assess opportunities and challenges regarding the use of artificial intelligence (AI) in public sector administration and policy development, focusing on whether AI can serve as a supplement and potential replacement for human policy analysts. The research questions focus on whether AI can plausibly ‘do’ policy analysis, support what human policy analysts currently do, and—based on those assessments—whether academia and governments need to reconsider … Lire la suite
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2014 — American Dreams: Portrayals of Race, Class, and 21st Century Capitalism in David Simon and Ed Burns’ The Wire,Résumé
From 2002-2008, the television series, The Wire, realistically conveyed the inner city problems of Baltimore, with a particular focus on the drug trade and its social and psychological effects on Baltimore’s black underclass. This dissertation values The Wire as a major achievement in television, for its sophisticated and intricate approach in exposing and critiquing systemic problems of inequality, disenfranchisement of the inner city black community, and bureaucratic dysfunction, and, in doing so, portrays the American Dream as a fallacy. By utilizing a Marxist ideological critique of late market capitalism I examine how The Wire positions Baltimore’s underclass in contention with … Lire la suite
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2024 — Historical accuracy in two video games: a study on reception theory and historical representation in Assassin's CreedRésumé
Historical video games are a class of video games set in the past, and these games are considered authentic representations of the past by players. An examination of female nonplayable characters (NPCs) in Assassin’s Creed: Origins and Assassin’s Creed: Odyssey using reception as a theoretical framework gauges the historical accuracy of the representations. While some aspects of the depictions were accurate, the accurate aspects were often supplemented with invented and inaccurate details, and other aspects were entirely ahistorical. Historical representations in video games have an impact on players’ understanding of the past, and because video games see regular graphical and … Lire la suite
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2012 — Female Sexuality And Intimate Partner ViolenceRésumé
Sexuality is a broad term that is used to include biological sex, sexual acts, sexual feelings, gender roles, and attitudes towards sexual behaviour (Jackson & Scott, 1996). It is a dynamic construct that can be influenced by many factors, including experiences of violence and abuse. Intimate partner violence (IPV) is one factor that can affect women in many ways, including their physical health, mental health, parenting, and sexuality (Burgess, 1983; Faravelli, Giugni, Salvatori, & Ricca, 2004). The focus of this qualitative study is to understand how IPV impacts women’s sexuality in a sample of women who have experienced IPV. A … Lire la suite
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2024 — Evaluating the effectiveness of analogies in an infographic on low-dose radiationRésumé
The aim of this research is to address misconceptions about Low Dose Radiation (LDR) by using analogies. The nuclear industry has shown that trust is asymmetrical, meaning it is easily lost and hard to regain. This was evident in Saskatchewan, where a public inquiry in 2008 revealed a significant lack of trust. Conversely, Saskatchewan possesses one of the largest uranium reserves globally, offering a carbon-neutral energy source. Additionally, it is increasingly cost-effective in the context of carbon pricing, making it an appealing option to fulfill the province’s energy and carbon objectives while ensuring energy security. The choice of analogies is … Lire la suite
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2022 — Public acceptance of facial recognition technology: Surveying attitudes, preferences, and concerns to inform policy developmentRésumé
One application of artificial intelligence (AI) in public sector governance is facial recognition technology (FRT), which is used to identify or discover individuals by comparing an image of their face to a database of known faces for a match. Along with these applications, however, concerns surrounding FRT use by governments have emerged as critics raise issues not only about the technology itself, but also the implications for the expansion of the ‘surveillance society’ and specific concerns such as demonstrated racial biases in FRT. While FRT continues to be developed and used, and governments struggle to develop a legislative and regulatory … Lire la suite
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2021 — A Comprehensive Evaluation of Off-Gas Emissions From A Catalyst-Aided, Amine-Based, Post Combustion Capture of CO2 From Industrial Exhaust Gas StreamsRésumé
The major focus of all CO2 capture technologies is to reduce emission of CO2 which is undoubtedly one of the major greenhouse gases blamed for global warming. It is imperative to ensure that while we aim to capture CO2 to achieve the production of clean energy, other contaminants are not released into our environment, so as not to defeat the main purpose of ensuring the safety of the environment. In the amine-based, catalyst-aided post combustion capture of CO2 technology, amine degradation occurs, and the degradation products are present in both the liquid and gas phases. It is important to know … Lire la suite
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2025 — Adaptive systems for DDoS attacks detection and mitigation in IoT networksRésumé
The rapid growth of IoT devices has revolutionized industries while exposing IoT networks to cybersecurity threats, particularly DDoS attacks, which compromise network stability. Traditional detection methods struggle to address the constraints of resource-limited environments, scalability, and the need for lightweight, optimized, and reliable systems. This thesis addresses these challenges through five objectives aimed at adaptive DDoS detection and mitigation systems for IoT networks, balancing accuracy, resource efficiency, and adaptability. The first objective focuses on developing a Flow and Unified Information-based DDoS detection system (FLUID) for small-scale IoT networks, enabling DDoS detection with minimal computational overhead. The FLUID system uses flow … Lire la suite
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2023 — Studying the background response of Minihalo for design optimizationsRésumé
The Neutron Detection Characterization Facility also called Minihalo Neutrino Detector is a planned research and development project that will enhance the detection capabilities of lead based neutrino detectors for supernova physics. It will will be used to construct low background He-3 counters for HALO-1kT supernova neutrino detector and will also provide experimental data on cross-sections of ν-Pb interactions at supernova energy scale. The detector will be placed at the SNS Facility in Oak Ridge National Laboratory on Oak Ridge, Tennesse, USA. The SNS Facility produces three ν species from impinging protons at liquid-mecury target. The νμ, ¯νμ, and νe are … Lire la suite
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2023 — Predictive visual servoing; uncertainty analysis and probabilistic robust frameworksRésumé
Motion control of robots in unstructured environments is a challenging task. The utilization of cameras as an information-rich sensor shows promise. In this context, image-based visual predictive controllers have gained attention due to their optimal-ity and constraint-handling capabilities. However, their performance deteriorates in presence of uncertainties in the robotic platforms, system models, and measurements. This work proposes a set of robust image-based visual predictive control methods that overcome the shortcomings of the previous visual servoing methods in the presence of uncertainties. In this dissertation, we have proposed a set of adaptive, stochastic, risk-averse, and learning-based visual servoing schemes that improve … Lire la suite
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2018 — Optimization of Blood Supply Chain Under UncertaintyRésumé
Blood supply chain is the resources used to provide patients with blood products during blood transfusing process at medical centers. The chain consists of blood donors at one end, blood collection stations to collect and produce blood products, storage equipment, transportation and patients who are in need for blood products on the other end. The demand in blood supply chain is random with a stochastic nature as it is the case in different products supply chain, however, the supply in this chain is also random and stochastic as blood donation process is a completely voluntary process. Meeting the random demand … Lire la suite
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2024 — Machine learning-based models for failure prediction and propagation in smart grid systemsRésumé
The smart grid connects components of power systems and communication networks in an interdependent two-way system that supplies or receives electricity to or from prosumers and collects data that enables it to react to usage levels and interference from threats, such as cyber-attacks. Cascading failures resulting from cyberattacks are one of the main concerns in smart grid systems. The use of artificial intelligence (AI)-based algorithms has become more relevant in identifying and forecasting such cascading failures. However, existing models that study the propagation of cascading failures either omit the impact of the communication network or power characteristics on the propagation … Lire la suite
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2023 — Problem recognition and treatment recommendations of somatic and cognitive-affective presentations of depression and generalized anxietyRésumé
Major depressive disorder (MDD) and generalized anxiety disorder (GAD) are among the leading causes of disability in the world; yet, rates of treatment seeking are exceptionally low. Poor mental health literacy is an important barrier to treatment seeking. One component of mental health literacy that impedes help seeking is poor problem recognition, or misidentifying a disorder and its symptoms when they are present. Although a wealth of research has established that accuracy of problem recognition is associated with help seeking related constructs (e.g., types of treatments recommended, intentions to seek treatment), no study to date has examined problem recognition of … Lire la suite
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2021 — Exploring Social Learning in Yorkton Following the 2010, 2014 and 2016 FloodsRésumé
The objective of this study is to explore whether social learning has occurred in Yorkton following the flood events that the City experienced in 2010, 2014 and 2016. The study also aims to understand the factors that impacted social learning’s occurrence, its interrelation with the window of opportunity, and the outcomes that it produced. The data for this study came from 15 semi-structured interviews and 110 newspaper articles on the flood events and the infrastructure upgrades. The data showed that the flood experience and the interactions and communications between the City, the Council and the public have produced social learning. … Lire la suite
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2020 — Motion Path Planning of Two Manipulators Working in a Common WorkspaceRésumé
Two robot arms working in a common workspace may collide because each of them is a dynamic obstacle for the other one. Motion Path Planning (MPP) is the process of finding a track that a robot/robot arm can follow to get to the target starting from any point in its workspace. In this Thesis, a collision-free MPP for two manipulators sharing a workspace is trained with reinforcement learning, specifically a Team Q-Learning algorithm, and two methods are considered for state discretization. For complicated models, a great deal of machine time is spent on calculation and decision making, while Look Up … Lire la suite
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2023 — Development of solvent for CO2 capture for utilization in concrete and storage in geological formationsRésumé
This study focused on developing an environmentally benign solvent for CO2 capture for utilization in concrete and the potential permanent storage in geological formations. Initial solvent screening and the selection included 2M aqueous solvents of KOH, NaOH, K2CO3, Na2CO3, sodium and potassium salts of glycine and lysine at 40oC and 20% CO2 balance nitrogen. The performance of the solvents was evaluated in terms of initial absorption rate, solvent precipitation and CO2 equilibrium loading. To present the best performing solvents as commercial products, the selected solvents were further optimized concerning solvent concentration, precipitation, CO2 partial pressure and absorption temperature. The absorption … Lire la suite
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2015 — Complexity Parameters for Learning Multi-Label Concept Classes,Résumé
In Computational Learning Theory, one way to model a concept is to consider it as a member of the Cartesian products of instances (sets), where each instance may correspond to a binary or multi-valued domain. A concept class is a set of concepts, and the goal of learning algorithms is to identify the target concept in a concept class from a small number of examples, i.e., labeled instances. This thesis studies multi-label concept classes and three important learning complexity parameters for these classes. The first parameter examined in this work is the Vapnik-Chervonenkis-dimension (VCD) and its previously studied analogues for … Lire la suite
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2021 — A Deep Learning Based Approach for Canola and Weed Segmentation in Precision AgricultureRésumé
Weeds are unwanted plants that can be eliminated using herbicides. Traditionally, these herbicides are sprayed uniformly which consumes an unnecessary amount and leaves adverse e ects on the environment. We can signi cantly cut this usage by selective spraying. It can be achieved using a decision map produced using eld images. Firstly, for all the images, classi cation is performed at the pixel level in either crop or weed. Then, the percentage of each class is calculated. Finally, these percentages are mapped using Global Positioning System (GPS) locations to generate a nal decision map for selective spraying. This thesis focuses … Lire la suite
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2023 — Developing a new approach for estimating oil recovery during Steam-Assisted-Gravity-Drainage (SAGD)Résumé
Canada possesses a substantial abundance of heavy oil and bitumen reserves. Given the continuously growing energy requirements, in conjunction with economic factors and expanding environmental issues, it becomes crucial to employ modern and economically viable techniques for extracting these subsurface resources. These methods not only demonstrate alignment with present requirements but also contribute to the long-term sustainability of the heavy oil business. Among the array of thermal procedures available, Steam-Assisted Gravity Drainage (SAGD) emerges as a highly promising approach for attaining substantial oil recovery. Despite the practicality of this technique and extensive research dedicated to it, there exists a notable … Lire la suite