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Principles of Credit
No full textIntroduction: In the Financial services industry, credit is a tool used by advisors and lenders to help consumer and business clients achieve their financial goals. In Principles of Credit, students will advise clients about consumer and business lending from the perspective of a lender/finance manager. Students will prepare credit proposals and present credit solutions for both consumers and businesses. Students will also learn how to communicate lending decisions with clients to ensure that financial loss and risk are mitigated
Remote Sensing: Improving Land Cover Classification using Satellite Signal and Deep Learning
No full textRemote sensing and land cover classification are useful tools for comprehending, monitoring, managing natural resources as well as environmental changes around the world. One key use of remote sensing is to accurately identify and classify different types of land, such as water bodies, flood-prone areas, farms, buildings, rice fields, roads, and construction sites. This plays a big role in helping with disaster response, monitoring agriculture, and using resources in a sustainable way. A key task is accurately segmenting satellite imagery and extracting features to identify regions of interest, using both optical and Synthetic Aperture Radar (SAR) data. However, remote sensing image segmentation presents several technical challenges, including limited availability of high-quality labeled datasets, high computational demands, class imbalance, cloud
obstruction, spectral similarity among crop types, and complexities due to spatial and temporal variations. Conventional index-based methods Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI) and traditional convolutional neural network (CNN) architectures, though widely used, frequently fall short under real-world complexities and specific sensor limitations such as cloud cover, seasonal changes, etc. Previous methods typically relied on conventional CNN architectures and straightforward thresholding methods, encountering major limitations in handling multichannel data fusion and class imbalance effectively. To address these issues, this thesis introduces several novel approaches successively. First, we propose the Fusion Adaptive Patch Network (FAPNET), designed to improve flood-water detection from SAR imagery by integrating adaptive multi-channel data fusion and innovative Neural Adaptive Patch (NAP) augmentation. This method significantly reduces computational demands while accurately segmenting water-affected areas. Building on this foundation, we further developed the Patch Layer Adaptive
Network (PLANET), a more advanced segmentation network dynamically adapting its structure to varying input resolutions. Furthermore, PLANET efficiently segments multiple land cover classes, addressing limitations found in previous conventional
CNN architectures by optimizing memory usage and enhancing segmentation precision. Recognizing that deep learning model training requires extensive labeled datasets often unavailable in remote sensing scenarios, we introduced Pixelwise Category Transplantation (PCT), an innovative data augmentation technique specifically tailored for water-body extraction tasks from Sentinel-2 imagery. PCT effectively reduces uneven class representation and boosts model learning by artificially increasing the amount of high-quality labeled data. Moreover, our thesis extensively investigates the use of spectral compositions and phenological stage information in agricultural land segmentation tasks, particularly focusing on rice crop identification. By conducting an in-depth assessment of the spectral band combinations from Sentinel-1 and Sentinel-2 imagery, we demonstrate that the appropriate selection of bands and temporal information significantly enhances segmentation precision, especially in complex agricultural landscapes.
This research provides significant contributions to the advancement of remote sensing-based land cover classification, introducing practical solutions to critical limitations inherent in current methodologies. Future research will further refine these models, utilize additional spectral and temporal information, extending their use to a wider range of environmental and agricultural remote sensing applications.
The main contributions of this research are given below:
1. In order to maximize the effectiveness of the learned weights, we introduce a multi-channel Data Fusion Module (DFM), which was created using Vertical transmit and Vertical receive (VV), and Vertical transmit and Horizontal receive (VH) polarization data. Also, elevation data from the NASA Digital Elevation Model (NASADEM), incorporating feature fusion, normalization, and end-to end masking, was used.
2. Inspired by CNN architectures, we developed a powerful data augmentation method called the NAP augmentation module. It extracts features at multiple scales using unit kernel convolution to create patches, helping the model learn faster and better understand the meaning of the data.
3. We propose FAPNET, which is a lightweight, memory-time-efficient, and high-performance model, as demonstrated in our quantitative and qualitative analysis.
4. The introduction of PCT, a novel form of data augmentation applicable not only to water body detection but also to a variety of generalized image segmentation tasks.
5. Introducing the PLANET model, which is an enhanced version of our previously proposed FAPNET model and the NAP-based data augmentation method, with an additional capability to handle multi-class segmentation.
6. Integrating the ability to dynamically generate segmentation encoder-decoder layers, providing simpler structures for smaller input sizes, and more complex structures for larger input sizes in order to achieve higher accuracy and efficient memory usage.
7. Design and implement robust methodologies to automate the mapping of irrigated rice fields using a median mosaic image composition
Precision and Efficiency Optimization of Robotics Coordination via Model Predictive Control
No full textThe thesis focuses on implementing Model Predictive Control (MPC) combined with Convolutional Neural Networks (CNN) for visual detection to optimize the trajectory of the Jackal autonomous vehicle and the Anafi drone. The objective is twofold: to achieve energy-efficient motion planning and precise tracking of a target drone. The MPC framework is designed to regulate the Jackal’s movement toward reference points with high accuracy while minimizing energy consumption. Meanwhile, the Anafi drone acts as a pursuing drone, utilizing the YOLO (You only Look Once) algorithm for real-time visual detection. Through onboard processing, the drone captures and uploads images of the target drone to an onboard laptop, where monocular camera images are used to calculate the 3D position of the target drone. The visual detection system leverages YOLO to train the Keypoints model, enabling the identification of the target drone’s Keypoints. The 3D position is then derived using the Perspective-n-Point (PnP) algorithm, which provides robust spatial information for the MPC to perform tracking.
By integrating MPC and CNN, this approach offers significant advantages over traditional PID (Proportional Integral Derivative) control. Specifically, it enhances tracking robustness under dynamic conditions and improves control precision by anticipating system states
Sex, Ethnicity and Clinical Outcomes in Autoimmune Hepatitis: Results from a Large, Multicenter, Longitudinal Cohort Study in Canada
No full textIntroduction: Autoimmune hepatitis (AIH) is a rare, chronic liver disease characterized by inflammation and immune-mediated damage of the liver tissue. AIH affects both sexes and all ages and ethnicities; although disease characteristics, progression and outcomes vary between these populations. The disease has an acute or chronic progressive course and may eventually lead to progressive liver fibrosis, cirrhosis and/or liver decompensation with some patients requiring a liver transplant (LT). Sex and ethnicity have been shown to affect the survival and clinical outcomes of other liver diseases; however, their influence on the progression of AIH is unclear. The aims of this thesis were to analyze the clinical significance of sex and ethnicity on treatment response and adverse clinical events in patients with AIH.
Methods: We conducted a retrospective and prospective cohort study of patients with AIH from the Canadian Network for Autoimmune Liver disease (CaNAL). CaNAL is a collaboration between 15 academic and clinical liver care centers across Canada to create a large, national registry of people living with autoimmune liver diseases including AIH. We collected key demographic variables including sex and ethnicity and clinical and outcome variables, such as laboratory parameters (alanine transaminase (ALT)), development of cirrhosis and liver decompensation, LT, hepatocellular carcinoma (HCC) and death. We defined an adverse clinical event as a composite endpoint that included the development of decompensation, LT, HCC or death. A univariate and multivariate Cox regression was conducted to examine associations between sex and ethnicity and adverse clinical events.
Results: Using a cohort of 1198 patients with AIH, we found that in comparison to females, males were younger at the time of AIH diagnosis (39.2 ± 19.5 vs. 45.0 ± 18.3 years, p<0.001); a higher proportion of males also developed HCC (4.0% vs. 1.8%, p=0.045) and underwent LT (19.3% vs. 9.1%, p<0.001). Male patients also demonstrated a lower treatment response compared to females (36.6% vs. 56.7%, p<0.001). In the multivariate analysis, male sex was associated with a higher risk for the development of an adverse clinical event such as liver decompensation, LT, HCC or death (HR 2.05, 95% CI 1.31-3.19, p=0.002). Compared to the White ethnicity, only Indigenous patients had a higher risk of developing an adverse clinical event in the multivariate analysis (HR 2.91, 95% CI 1.04-8.16, p=0.043). A greater proportion of Indigenous patients also had decompensation at diagnosis (23.5% vs. 8.5%, p=0.008), developed decompensation over the course of the disease (34.6% vs. 18.0%, p=0.040), underwent LT (26.5% vs. 11.3%, p=0.013) and died (26.5% vs. 13.0%, p=0.036) compared to non-Indigenous patients, but there was no significant difference in treatment response (60.0% vs. 51.4%, p=0.752).
Conclusions: Male patients with AIH have a higher risk of developing adverse clinical events such as liver decompensation, HCC, LT or death and have a lower treatment response compared to females. From the ethnicity perspective, Indigenous patients with AIH have a higher risk of developing adverse clinical events compared to other ethnicities. Our results warrant consideration of tailoring treatment and follow-up strategies according to risk stratifications by sex and ethnicity in order to improve clinical outcomes and survival for at-risk groups, such as males and Indigenous patients
Daramend® in the Remediation of Bromacil in Surface Soil
No full textUntil the early 1990s, bromacil was frequently applied on industrial sites within Alberta as part of total vegetation control practices. Bromacil is a brominated organic compound that is used as a non-selective, persistent herbicide. Due to its persistence after frequent applications, bromacil concentrations in soil on these industrial sites remain above Alberta Tier 1 Soil and Remediation Guideline limits. As these sites reach the end-of-life, industry owners and government regulators are addressing the challenge of remediating bromacil in soil. Since bromacil is highly soluble and has low sorption to soil, it often migrates with surface and groundwater flow, impacting soil off-site, and risking freshwater aquatic life receptors. Anaerobic biodegradation is the primary mechanism that degrades bromacil through reductive debromination. The reductive debromination process removes the bromine atom from bromacil, producing the byproducts bromine ions and 3-sec-butyl-6-methyluracil that are less toxic than bromacil. Reductive debromination is a similar reductive dehalogenation process that is used in the remediation of chlorinated organic compounds. The dehalogenation of chlorinated organic compounds can be done by anaerobic biodegradation or through reductive chemical processes. Common remediation technologies include the use of zero valent iron (ZVI) to abiotically remediate chlorinated organics through reductive dehalogenation.
In 2019, the Soil Sterilants Program (SSP) was established to address the challenges associated with bromacil, including identifying and testing bromacil remediation technologies. The research in this thesis is a subset of the remediation experiments conducted by the SSP.
The SSP identified Daramend®, a remediation soil amendment composed of organic matter and ZVI, as a potential technology to remediate bromacil in soil. Currently, it is used in the remediation of chlorinated organic compounds in soil, including chlorinated herbicides. Daramend® remediates chlorinated organic compounds through a combination of anaerobic biotic and abiotic reductive dehalogenation. Bench- and meso-scale testing conducted by the SSP showed that Daramend® can degrade in bromacil in soil. For this thesis, a series of experiments were conducted to evaluate how Daramend® degrades bromacil in soil under anaerobic conditions and to assess its performance in meso-scale settings. The hypothesis was that Daramend® would degrade bromacil at lab and meso-scales through a combination of abiotic and biotic mechanisms. The research objectives were to: (1) identify whether degradation of bromacil in soil amended with Daramend® was one or a combination of abiotic and biotic mechanisms; (2) identify the Daramend® optimal dosage and water application frequency for the remediation of bromacil in surface soil; and (3) determine if Daramend® can effectively remediate bromacil in surface soil in a meso-scale study.
Results from these experiments found that: (1) Daramend® can enhance bromacil degradation and can degrade limited amounts of bromacil abiotically, but (2) maintaining sufficiently anaerobic conditions can degrade bromacil without additional amendments, and (3) maintaining sufficiently anaerobic conditions in surface soil at field scales is not feasible in surface soil. Below ground bromacil impacts pose a greater challenge in Alberta. Despite being under anaerobic conditions, bromacil in the groundwater zone often does not degrade. Injecting Daramend® or similar organic amendments into the contaminated zone or installing as a permeable reactive barrier may initiate biodegradation of bromacil in the below ground, saturated zone
Magnetotelluric Data from Northern Alberta
No full textArchive for the magnetotelluric data that was collected and used in a study in Northern Alberta.
See README for details on the files
Three Essays on Superstar CEO
No full textThis thesis explores the dynamics of the superstar system, which is characterized by a highly skewered distribution of compensation and increased public attention to a small group of CEOs, through three essays that integrate agency theory, managerial myopia theory, social status theory with decision-making process. It investigates the unique characteristics of superstar CEOs, defined by a group of CEOs that have won at least one prestigious business award, focusing on the role of the superstar status in firms adopting different accounting practices, conducting mergers and acquisitions, and CEOs competing in the labor market. The first essay investigates how winning a prestigious award affects CEO’s personal trait. The findings show that superstar CEOs, compared with their matched non-winning CEOs, tend to be more overconfident after winning their first award. In response to superstar CEOs’ increasing incentives to overstate gains and understate losses, more conservative financial reporting standards are used by the winning firms. The more conservative accounting practices are shown to mitigate the problem of superstar CEOs’ overconfidence, firms where both characteristics, superstar CEO and accounting conservatism, are present perform better than the firms without the two characteristics.
The second essay provides an updated analysis of mergers and acquisitions, revealing that a CEO’s social status plays an important role in explaining firm’s merger decisions. Firms led by superstar CEOs conduct more intensive merger activities, where the superstar status is associated with increased level of M&A activity. The effect is particularly strongest two years and three years after CEOs winning their first award. Moreover, superstar CEOs are more likely to undertake risky mergers and acquisitions such as cross-border and cross-industry mergers, compared with their non-winning competitors.
The third essay examines the influence of winning an award on the CEO’s competition in the labor market, arguing that superstar CEOs experience more job changes. Through an analysis of post-award career movements, it shows that superstar CEOs are more likely to gain additional job titles, including board memberships, advisory positions, and leadership roles at both their current and new firms. The findings suggest that prestigious awards do more than honor past success—they actively shape a CEO’s future career path by increasing visibility, expanding professional networks, and enhancing perceived value in the labor market. Winning a prestigious CEO award is often seen as the pinnacle of executive recognition, signaling exceptional leadership and talent. However, beyond prestige, such accolades may also cast a curse on firms. This thesis examines the relationship between CEO award recognition and subsequent changes in CEO’s personal trait, behavior and corporate outcomes. Drawing from behavioral finance theories, this research emphasizes the critical role of CEO’s superstar status in corporate decision making and contributes to the broader understanding of the influence of CEOs’ social status on their behaviors
Shaista Meghani - Abstract 53 - Innovate Conference 2025
No full textHospitalization in the ICU can have long-term physiological and psychological impacts, affecting functional recovery and quality of life of post-ICU patients. Despite systematic reviews showing the impact of music interventions on physiological and psychological outcomes in ICU patients, their applicability and effectiveness in the post-ICU context remain unclear
Therapists’ Lived Experiences of Recognizing and Addressing Microaggressions Towards Their Clients
No full textDespite training and personal efforts, psychologists and other mental health professionals often engage in microaggressions towards clients during therapy. Microaggressions refer to comments, behaviours, or actions that dismiss and/or belittle aspects of one’s diverse identities (Sue et al., 2007, 2022). These facets of identity include areas such as race, gender, ethnicity, sexual orientation, gender identity, religion, immigration status and disability. Within the context of therapy, microaggressions are particularly problematic: equity denied clients courageously reaching out for support face yet another space where they are insulted, dismissed, and/or rejected. Unfortunately, many studies show that microaggressions negatively impact therapeutic relationships and, in some cases, lead to premature termination of therapy (Carone et al., 2023; Owen et al., 2019). Client-based research shows that discussing microaggressions can mitigate the harm caused. Unfortunately, no studies have explored exactly how microaggressions are addressed in therapy. Further, there is no research on therapists’ perspectives and experiences of engaging in microaggressions towards clients. The purpose of this study was to explore how psychologists recognized and addressed microaggressions they perpetrated in therapy using Smith et al.’s (2022) Interpretative Phenomenological Analysis (IPA) approach. Five Canadian psychologists (registered or on-track for licensure) were interviewed about their experiences. Eight group experiential themes which highlighted participants’ experiences were found: sensing a shift in therapy; calling out the microaggression; the embodied experience of microaggressing; experiencing self-judgement; navigating unknowns in therapy; preparing oneself to address the microaggression; owning up to the microaggression; and, monitoring cues for resolution