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Family and Justice in the Archives: Historical Perspectives on Intimacy and the Law
Get PDFLegal archives offer extraordinary opportunities for understanding intimacies across time and space. Family and Justice in the Archives presents a series of fascinating historical essays that unpack stories of familial, domestic, and sexual intimacy from the records left behind by legal processes, providing rich new insights about family, gender, race, sex, culture, identity, and daily life.
Contributors examine the written traces left by public proceedings that occurred in legally sanctioned spaces of social regulation, from notaries’ offices to criminal and civil courtrooms to legislatures. Focusing on the past two centuries and spanning five continents, the essays explore a wide range of topics including marriage, citizenship, inheritance, indentured servitude, infanticide, juvenile justice, parental abuse, bigamy, and sex work. Mindful of the ethical questions that arise when scrutinizing the details of people’s most vulnerable moments, these authors also demonstrate how individuals navigated and sometimes challenged legal prescriptions and processes to address systemic imbalances of power.
Family and Justice in the Archives reveals the wealth of detail that emerges from a close reading of documents generated by legal processes in the past, offering valuable new perspectives on the complex personal lives of so-called ordinary people in former times
Tracings: Writing Art, 1975-2020
Get PDFAn artist, curator, critic, and teacher, Ian Carr-Harris has been a central figure in Toronto’s art scene since the 1970s. By collecting his impressive output of essays, critical experiments, and reviews into a single volume, Tracings documents the growth of conceptual art and postmodernism in Canadian art, as well as the expansion of mediums and spaces, while providing insights into methods of representation and the role of criticism in contemporary art.
In clear and intelligent prose, Carr-Harris offers detailed studies of individual artists and exhibitions as well as theoretically informed reflections on broader cultural concerns. Whether writing about the complexities involved in the construction and transmission of knowledge, meaning, and historical narrative, or discussing the material matters of government cultural funding, patronage, and artist-run centres, or describing his own process and artworks, these pieces reveal a literary love of language and a nuanced and investigative mind at work. Throughout his writing, he considers themes of identity, cultural nationalism, postcolonialism, institutionalism, the act of viewing, and relations of power.
An introduction by Dan Adler situates Carr-Harris’s work within the context of his contemporaries, collaborators, and cultural environment, pointing out the mutually reinforcing qualities and relationships between his art and his writing. Covering decades of critical thought and engagement, Tracings confirms why Ian Carr-Harris has indelibly written himself into Canadian art
Investigating the Vocabulary Spurt in Bilingual and Monolingual Infants
Get PDFSometime before their second birthday, many children have a period of rapid expressive vocabulary growth called the vocabulary spurt. Theories of the underlying mechanisms differ: accumulator models emphasize the accumulation of experience with words over time to yield a spurt-like pattern, while cognitive models attribute the spurt to cognitive changes. To test these theories, English–French monolingual and bilingual children with different exposure to each language were studied. Dense, longitudinal data was analyzed from 45 infants aged 16-30 months, whose expressive vocabulary was measured on a total of 617 occasions in English and/or French. Single-language (English and/or French), concept (number of concepts lexicalized across both languages), and word (sum of both languages) vocabulary scores were computed. Infants’ exposure to each language and their exposure balance were measured using a language exposure questionnaire. Logistic curves were fitted to each infant’s data to estimate the timing (midpoint) and steepness (slope) of the vocabulary spurt in single-language, concept, and word vocabularies. 76% of infants showed a spurt in at least one vocabulary type, and bilinguals were less likely to show one in their non-dominant than their dominant language. For single-language vocabulary, infants with more exposure to a language had earlier spurts. For combined vocabularies (concept and word), monolinguals and unbalanced bilinguals had earlier and steeper spurts than balanced bilinguals. Results better support the predictions of accumulator models than cognitive theories, and show that infants follow different vocabulary acquisition trajectories based on their language background
Model Checking the Interplay of Trust and Commitments in Multi-Agent Systems and Applications
Get PDFEffective communication among agents in open multi-agent systems (MASs) is crucial for their development. Agents operate autonomously within unpredictable environments, necessitating consideration of security, social, and communicative modalities. Trust and social commitments are pivotal in modeling secure communication mechanisms. While efforts have been made to define their semantics separately, a deeper exploration of their connection is needed.
IoT and ad hoc networks have introduced novel service models in multi-agent applications, but effective communication remains essential for coordinating various components. This cooperation enables addressing challenges exceeding individual capabilities. Ensuring component reliability is a primary concern, particularly with entities prone to malicious behavior.
Trust often varies in strength and depends on factors like past experiences and transparency. Critical systems rely on strong trust for data security and privacy, entrusting them with significant responsibilities.
This thesis proposes three verification approaches: 1) a framework, TCTLC, for handling trust over social commitments using the Model Checker for Multi-Agent Systems (MCMAS); 2) a three-valued trust model for uncertain IoT-ad hoc settings, validated through case studies in smart health monitoring and smart homes; and 3) a novel logic, TwsCTLC, capturing weak and strong trust over commitments in MASs, validated through a scalable case study.
These contributions aim to advance trust and commitment management in MASs and enhance IoT reliability in smart environments, providing practical tools for uncertain scenarios
Detection of Cyberattacks for Enhancing Security of Cyber-Physical Systems
No full textA Cyber-Physical System (CPS) refers to a physical system that integrates control, computational and communication capabilities. Indeed, CPSs find applications in various domains, including autonomous vehicles, water distribution systems and the Internet of Things (IoT). While CPSs offer potential for enhancing traditional engineering systems, security concerns regarding cyberattacks have become prominent. A key objective for potential attackers is to remain stealthy. In this dissertation, we focus on the development of detection methods to detect intelligent and malicious adversaries in CPS. The detection methods entail intelligently designing and altering the system’s architecture to hinder adversaries from executing stealthy attacks.
First, a novel architecture aimed at detecting replay cyberattacks is introduced. This solution is implemented by integrating a virtual auxiliary system and detection filters into the automated control system. The incorporated filters effectively isolate replay cyberattacks from other forms of adversaries. Furthermore, our solution demonstrates proficiency in maintaining the closed-loop performance of the system.
Second, a novel method for detecting Pole Dynamic Attack (PDA), is proposed. The adverse effects of PDA attacks on a CPS are analyzed. To tackle this issue, the physical system is enhanced by adding an auxiliary system on the plant side and its duplicate, along with incorporating detection filters into the command and control Center. Furthermore, our novel defense mechanism exhibits robustness in detecting PDA attacks across diverse levels of attacker knowledge and capabilities.
In conclusion, the exploration of enhancing the security of CPS by intelligently adjusting the system’s architecture to hinder an adversary’s ability to carry out stealthy attacks is presented in this thesis
Economic Assimilation of Immigrants in Quebec
Get PDFIn this paper, I examine the wages and work hours of immigrants in Quebec and the rest of Canada. By analyzing data from the Survey of Labour and Income Dynamics (SLID) for the years 1999 to 2011, I explore three key questions about the economic integration of immigrants relative to native-born individuals. The first question examines the initial wage gap for new immigrants, defined as those who have lived in Canada for less than ten years at the time of data collection. The second question assesses whether this wage gap changes significantly over the sample period. The third question examines the extent of economic assimilation in immigrant earnings as their residency in Canada lengthens. The findings reveal a significant initial wage gap, with new immigrants earning 28.8% less than their native counterparts. Over the sample period, this gap narrowed by 1.3% annually. Additionally, the analysis indicates that economic assimilation is substantial, though rates vary between Quebec and the rest
of Canada. Initially, assimilation occurs more quickly in Quebec, whereas over time, immigrant earnings rise more rapidly outside Quebec. To further explore the economic assimilation of immigrants, I investigate their work hours and find that new immigrants work fewer hours than their native counterparts. As with the wage gap, the immigrant-native gap in work hours narrows as immigrants stay longer in Canada. To understand these assimilation effects on both wages and work hours, I analyze a simple model of learning by doing (LBD) and show that the model can account for the key observed patterns of wages and hours worked among immigrants in the SLID
Neural Real-Time Recalibration for Image-based Multi-Camera Systems
Get PDFTraditionally, multi-camera calibration relies on physical objects and a controlled environment to achieve high-accuracy results, but this cannot be extended to real-time. Recent advancements in deep learning (DL) have enabled image-based camera calibration, offering real-time operation but
often sacrificing accuracy for speed. In this thesis, we address this trade-off by proposing a novel approach that leverages DL models for online and real-time multi-camera calibration with high precision. Current DL methods for camera calibration, while fast, often struggle with real images
captured in the wild due to varying conditions. Our approach tackles this challenge by introducing a deep learning model designed for online calibration scenarios from images with low inference time.
This model adapts to various camera poses efficiently, ensuring robust calibration across diverse viewpoints.
Central to our approach is the introduction of perturbations into the camera parameters, leveraging known initial parameters and 3D fiducial coordinates. This technique allows the model to learn and predict accurate camera parameters even in uncontrolled settings. Extensive experiments demonstrate the effectiveness of our proposed approach, particularly in scenarios requiring real-time calibration with high precision
Two Essays on Corporate ESG Disclosure
No full textThis dissertation consists of two essays relating to corporate ESG disclosure. The first essay examines the predictive value of forward-looking statements (FLS) in ESG reports issued by U.S. public firms. I predict that the disclosure level and linguistic features of FLS in ESG reports contain information about future ESG performance. To examine this prediction, I collect a sample of ESG reports issued by U.S. public firms from 2000 to 2019. The empirical tests show that a higher disclosure level of FLS and a more positive tone of FLS are associated with lower future ESG performance. I also find that more specific FLS and less boilerplate FLS are associated with higher ESG performance in the future, indicating that higher-quality disclosure signals better future performance. This study advances our understanding of forward-looking information in ESG. All findings are robust to specifications that consider alternative measures. The second essay examines whether board ESG expertise is associated with the usefulness of ESG reports. I posit that board ESG expertise plays a pivotal role in shaping the company’s ESG disclosure, aligning it with firm performance, stakeholder expectations and regulatory requirements. To examine this prediction, I collect a sample of ESG reports issued by U.S. public firms from 2002 to 2021. Consistent with my predictions, I find that board ESG expertise is associated with the disclosure of material ESG information, less positive ESG disclosure tone, more specific ESG disclosure, and more year-over-year modifications in ESG reports. Difference-in-differences analysis, falsification tests and lagged regression analysis support the main findings. The results indicate that a board of directors with ESG expertise enhances the usefulness of ESG reports. In both essays, we gain critical insights into the predictive value and usefulness of ESG reports, revealing how the quality and characteristics of forward-looking statements and the presence of board ESG expertise significantly shape the predictive value and usefulness of these disclosures
Deformation of Convex Hypersurfaces in Euclidean Space by Powers of Principal Curvatures
Get PDFThe results presented in this thesis contribute to the understanding of the evolution of smooth, strictly convex, closed hypersurfaces in driven by non-symmetric speeds on the principal curvatures. The preservation of convexity, the occurrence of singularities, and the asymptotic behavior of the flows are studied.
After an introduction to geometric flows, Chapter 3 focuses on the analysis of the short-term and long-term behavior of a contraction flow governed by a non-symmetric speed for rotationally symmetric hypersurfaces. Our investigation reveals two key findings. Firstly, we establish that the flow maintains convexity throughout the deformation process. Secondly, we observe the development of a singularity within a finite time, leading to the convergence of every such strictly convex hypersurface to a single point.
To investigate the asymptotic behavior of the flow, we employ a proper rescaling technique of the solutions. Through this rescaling, we demonstrate that the rescaled solutions converge subsequentially to the boundary of a convex body. In the fourth chapter, we extend our study to the short-term and long-term behavior of a non-symmetric expansion flow in . We show that, starting with a smooth, strictly convex, rotationally symmetric, closed hypersurface, the flow preserves convexity while expanding infinitely in all directions. Depending on certain parameters within the speed function, we establish that the existence time of the flow can be either finite or infinite. We also investigate the asymptotic behavior of the flow through a suitable rescaling process and demonstrate the subsequential convergence of the solutions to the boundary of a convex body in the Hausdorff distance. In the fifth chapter, we introduce the most general version of the flow studied in the Chapter 3. We address the barriers and challenges encountered when transitioning from a symmetric speed to a non-symmetric speed, and present our strategies to tackle some of these difficulties
Online Condition Monitoring of Stator Winding Insulation State of Electric Machines in Electrified Vehicles
Get PDFElectrified vehicles commonly use traction machines powered by voltage source inverters (VSI) for efficient speed and torque control. However, short circuit faults and insulation failures remain prevalent, accounting for approximately 30% of motor failures. Given the uncertainties surrounding insulation degradation, detecting degradations of insulation in an early stage can help prevent major failures. Therefore, this Ph.D. research focuses on online monitoring of electrical machine’s winding insulation degradation.
A comprehensive review of literature revealed certain research gaps. The first one is on selection of the most effective insulation degradation indicator for online condition monitoring without increasing motor drive costs. To address this challenge, this research uses existing signals in EV motor drives, such as line current measurements. However, there is limited information on how insulation degradation can impact the line currents in the existing literature. Therefore, this Ph.D. work address this knowledge gap through conducting investigations of insulation indicators. It is found that the antiresonance oscillations in line current can serve as indicators for insulation degradation, which was not reported in the existing literature.
Existing literature on condition monitoring methods also presents notable limitations. Firstly, these techniques can not determine the degradation of groundwall (GW) or turn-to-turn (TT) insulations simultaneously. There is a need for a new approach for simultaneous condition monitoring of TT and GW insulations. This is crucial because different types of insulation are exposed to different temperatures, leading to a varied degradation rate. Additionally, current methods overlooked the variability of noise in measured signals, which can fluctuate due to various factors in real-world applications like EVs. This variability necessitates a condition monitoring approach that can handle noise while accurately determining insulation health. Moreover, existing methods rely on predefined thresholds and manual analysis, requiring expert interpretation, which limits their applicability across different machines and conditions. Hence, this Ph.D. work proposes novel methodologies to address these limitations. A technique for simultaneous monitoring of TT and GW insulation conditions has been proposed. To address the limitation posed by noise variability and the reliance on manual analyses, a novel data-driven methodology for robust insulation condition monitoring has been proposed