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Getting Ready for the Real World: Final-Year Students and Their Virtual Recruitment Event Experiences
Get PDFResearch problem:
This study explores the experiences and perceptions of final-year undergraduate business students at a comprehensive university in central Canada regarding virtual recruitment events and their role in networking and advancing career opportunities for soon-to-be graduates. Although virtual recruitment events (activities that occur online to bring together employers and job seekers) have become more common since the COVID-19 pandemic, little research has focused on the student perspective of these events.
Research questions:
1. What are the expectations and perceptions of university students regarding networking and advancing their job search?
2. What are the expectations and perceptions of university students regarding virtual recruitment events?
3. How do university students perceive the relationships between virtual and in-person events?
a. Are virtual events seen as complementing or replacing in-person events?
b. What are the strengths and limitations of virtual recruitment events?
4. How do virtual events support university students in forming social networks necessary for effective career advancement?
Literature review:
Social Network Theory and Weak-Tie Network Theory provide a foundation for understanding how relationships influence job search outcomes, with an emphasis on weak-tie (casual, infrequent) connections in accessing new opportunities. Genre theory helps explain how students interpret and engage with recruitment events based on familiar communication norms. Virtual events, while offering accessibility benefits to attendees, raise concerns about engagement and connection. Career Services play a key role in organizing these events, preparing students, and adapting formats to meet evolving needs.
Methodology:
This qualitative study used a collective case study approach. Five final-year undergraduate business students or recent graduates from a comprehensive university in central Canada were selected through purposive sampling. They were interviewed using semi-structured interviews, which were analyzed using thematic analysis following Braun and Clarke’s (2006) six-step method.
Results and Conclusions:
The findings suggest that students view networking as critical to job search success and career advancement. Although virtual recruitment events offer convenience and accessibility, participants agreed that they complement, but do not replace, in-person events. Virtual events are useful for gathering information, but students rely more on in-person experiences to build strong professional relationships. Additionally, the findings suggest that networking is a skill developed through practice, that intentional efforts made by Career Services and recruiters can support students in building their professional networks
Finite-data Error Bounds for Approximating the Koopman Operator
No full textThe Koopman operator is a powerful tool for the study of dynamical systems that allows the study of nonlinear systems through the lens of observables functions forming an equivalent linear formulation of the dynamics in an infinite-dimensional space. Recent developments in data-driven approximation techniques allow the approximation of the Koopman operator without any a priori knowledge of the underlying system. However, despite the existence of asymptotic results on the capabilities of such techniques, only a few guarantees exist in the more realistic finite-data setting.
Approximation of the Koopman operator through Extended Dynamic Mode Decomposition (EDMD) has been observed to converge at the Monte Carlo rate of the inverse, i.e., proportionally to the square root of number of samples. In this thesis, we bridge the gap between EDMD and the theory of least squares to provide a proof of this statement with minimal assumptions. Moreover, leveraging known results from function approximation via least squares, we investigate the effect of the sampling routine and the choice and size of dictionary on the convergence of the EDMD method. Additionally, we develop a similar approach in the context of compressed sensing, where we provide recovery guarantees when the Koopman operator is sparse. Finally, we validate theoretical findings through extensive numerical illustrations
Violations of the self and mental contamination: A multimethod investigation
No full textMental contamination refers to contamination-related symptoms, common in obsessive-compulsive disorder (OCD) and in survivors of sexual trauma, that arise in the absence of direct contact with a physical contaminant. Cognitive models of mental contamination highlight the central role of perceptions of violation in the onset and maintenance of these feelings. That said, little research has been conducted to operationally define the construct of violation and systematically examine its different manifestations. Maladaptive appraisals of the self have been identified as maintaining factors in cognitive models of both posttraumatic stress disorder (PTSD) and obsessive-compulsive disorder (OCD). Thus, perceptions of violation of one’s self-concept may represent an aspect of violation appraisal relevant to the experience of mental contamination. The aim of the proposed program of research was to expand upon key components of this model using a multimethod approach. Study 1 involved a qualitative analysis of the experience of violation in a sample of 20 participants with OCD and/or trauma histories. Three overarching categories emerged from the interviews, each with several themes and sub-themes – qualities of violation, violation-related appraisals, and violation-related behaviour. Specific self-focused appraisal sub-themes (i.e., permanence of consequences; self-worth; and responsibility, self-blame, and regret) were most closely related to emotions tied to mental contamination. Following from the results from Study 1, Study 2 comprised the development and validation of a novel self-report questionnaire of violation appraisals, the Violation Appraisal Measure (VAM). Results from validation in an undergraduate sample (N = 300) suggested a four-factor structure for the VAM, which was confirmed in a second undergraduate sample (N = 300) and sound psychometric properties were demonstrated. Study 3 consisted of an experimental manipulation of perceptions of moral self-violation in a sample of undergraduate students (N = 150). Overall, self-violation, as compared to self-bolstering and a negative mood induction, led to heightened mental contamination feelings, but not heightened urges to wash. Theoretical and clinical implications of these findings are discussed
Navigating decentralized finance (DeFi) risks and challenges through user-centric solutions
No full textThis dissertation explores the evolving landscape of decentralized finance (DeFi), addressing critical challenges such as scalability, consumer protection, front-running, and stablecoin stability. By bridging the gap between technological advancements and regulatory needs, the research provides innovative solutions to enhance DeFi’s accessibility, security, and scalability.
The study investigates fast withdrawal mechanisms in optimistic rollups, enabling users to bypass the traditional seven-day dispute period through tradeable exits. By implementing and analyzing these exits on platforms like Arbitrum, the work evaluates their efficiency, scalability, and risks, offering practical insights into dispute management.
Decentralized order books form another key focus, with a detailed examination of their feasibility, performance, and front-running vulnerabilities. Through the implementation of the Lissy exchange on Ethereum and Layer 2 solutions, the research demonstrates significant improvements in gas efficiency and scalability while proposing novel strategies to mitigate transaction manipulation.
The dissertation also provides a systematized framework for understanding stablecoins, categorizing their stability mechanisms and highlighting vulnerabilities. This analysis lays the groundwork for assessing their role in mitigating volatility and enhancing financial inclusion.
Overall, this work contributes to DeFi’s maturation by addressing technical and regulatory challenges, ensuring user centric design while promoting financial innovation. The findings aim to align DeFi with consumer protection frameworks, paving the way for its broader adoption as a reliable alternative to traditional financial systems
The cognitive mechanisms underlying early school readiness and achievement: cross sectional and longitudinal examinations
No full textUnderstanding the factors contributing to early school success is an important way we can help foster children’s development. Although several social and cognitive factors contribute to children’s success at school, this dissertation focused on two cognitive skills: executive functions (i.e., the ability to plan and execute tasks) and metacognition (i.e., knowing our thoughts). These skills have been consistently linked to academic achievement in different capacities, but have rarely been directly compared. To this end, the two studies included in this dissertation present data from the same cohort of children, first in kindergarten and then in first grade, whose academic abilities, as well as executive function and metacognition, were measured. The first study looked at the cross-sectional relation between the variables. The second study focused on the cross-sectional results at time 2 and the longitudinal relationships between the variables. Based on the available literature, we expected both cognitive skills to be related to academic abilities, with metacognition emerging as the stronger predictor.
Both studies measured executive functions with tasks measuring inhibition and shifting abilities. Metacognition was measured by asking children to rate their confidence levels after answering questions, inquiring whether they wanted help answering, and recording the time it took them to provide an answer.
The first study measured school readiness using the Lollipop task, which assessed children’s basic literacy and numeracy skills. Results suggested a significant relation between verbal metacognition measures (confidence and request for help) and school readiness. The second study measured academic achievement using the reading and mathematics scales from the Weschler Individualized Achievement Test (WIAT-III, WIAT-II-FR). Concurrent results suggested a strong link between executive functions and academic achievement. Longitudinal results identified school readiness as a powerful predictor of academic achievement, as well as an indirect link between executive function scores at time 1 and academic achievement results at time 2, through executive function scores at time 2, suggesting cognitive abilities in the kindergarten year can partially predict academic performance one year later. Taken together, these results indicate that the relations between cognitive and academic skills are complex and changing in the early school years
Intent-Based Service Graph Generation and Selection for Cost-Effective Service Deployment in the Cloud
No full textCloud computing provides a wide range of virtualized services, such as computing power, storage, and applications, which can be accessed on-demand. Cloud-native applications are built using a microservices architecture, where independent, function-specific services communicate through APIs and messaging protocols. Service graph is a directed graph that shows interaction and dependencies between these services. An application can be achieved by using different services with same functionality which result in having multiple service graphs. However, selecting an optimal service graph among all possible ones is a challenging task that requires expertise in cloud applications, their dependencies, and compatibility, along with meet non-functional requirements such as bandwidth, and latency. Tradition
approaches rely on domain experts who manually generate service graphs, a time-consuming and error-prone approach
that often results in suboptimal configurations, higher deployment costs, and unmet performance criteria. These challenges highlight the need for automated solutions to efficiently produce optimal service graphs aligned with cloud consumers expectations.
Intent-Based Networking (IBN) is a new paradigm that allows cloud consumers to specify their requirements at a
high level, without dealing with the underlying technical complexities. Intent is a request at a high-level of abstraction (e.g., Natural Language), which describes what the cloud consumers expect. More specifically, it enables cloud consumers to focus on defining ”what” they need, such as performance targets, cost constraints, or latency requirements, without needing to specify ”how” these objectives should be achieved. Instead of manually selecting and configuring services, cloud consumers express their intent in terms of objectives such as performance targets, cost constraints, or latency requirements. Then, these high-level intents translates into low-level configurations, automatically generating and deploying the service graph in the cloud.
In this thesis, we address the problem of service graph generation and selection while considering both functional and non-functional requirements derived from cloud consumer intent. Our objective is to minimize the total deployment cost of the service graph in a data center network and to determine its placement within the distributed data center network. To address the problem, first, we translate high-level intent using a domain ontology into its functional and non-functional requirements which are specified in terms of initial services, latency, and bandwidth. Then, we use a service catalog along with the initial services to generate all possible service graphs that can meet the functional
requirements of the given intent. We formulate the problem as an Integer Linear Programming (ILP), taking into account the bandwidth and latency requirements of the intent. To solve this, we propose our Service Graph Selection (SGS) solution, which aims to achieve a near-optimal solution in a computationally efficient manner. Our results demonstrate that the proposed solution achieves a deployment cost that is only 4-6% larger than the lower bound of the optimal deployment cost
Rare-Earth Metal–Organic Frameworks with a Pyrene-Based Linker for the Photooxidation of a Sulfur Mustard Simulant
No full textMetal–organic frameworks (MOFs) have been extensively studied in the last few decades for their potential application in gas adsorption, water capture, catalysis, and others. Metals from the d-block on the periodic table are often applied in MOF synthesis, however, rare-earth (RE) metals, which include scandium, yttrium and the series of fifteen lanthanoids, have also been explored due to the intricate structures and specific properties that RE-MOFs can feature. The chemical warfare agent, sulfur mustard (HD), still exists in stockpiles in different countries and can be easily synthesized by nations under armed conflict. RE-MOFs are promising to study for the sustainable detoxification of HD.
This work exposes the synthesis and characterization of four isostructural series of RE-MOFs obtained using a tetratopic pyrene linker (H4TBAPy) and named RE-CU-04, RE-CU-05, RE-CU-06, and RE-CU-10 (RE = Sc(III), Y(III), La(III), Ce(III), Pr(III), Nd(III), Sm(III), Eu(III), Gd(III), Tb(III), Dy(III), Ho(III), Er(III), Yb(III), Tm(III), or Lu(III); CU = Concordia University). The structure of RE-CU-04 and RE-CU-05 are explored by total X-ray scattering, followed by pair distribution function (PDF) analysis to resolve the local structure of the RE node. Electron diffraction data collected from RE-CU-06 microcrystals indicate a structure with rhombohedral channels and RE chains with frl topology. Single crystal X-ray diffraction (SCXRD) of RE-CU-10 reveals a structure comprised of 12-connected RE9-cluster SBUs, with shp topology, featuring 1D triangular channels.
The accessible surface area of these new MOFs and the ability to generate singlet oxygen using the pyrene-based linker under ultra-violet (UV) irradiation, makes RE-CU-04, RE-CU-05, RE-CU-06, and RE-CU-10 good candidates for the selective photooxidation of HD, where the simulant 2-chloroethyl ethyl sulfide (2-CEES) is oxidized to its less toxic sulfoxide, 2-CEESO. RE-CU-10 shows one of the best photooxidation performances for 2-CEES to 2-CEESO among all pyrene-based MOFs reported, achieving 100% conversion within 15 min. RE-CU-05 and RE-CU-06 feature a slower performance, reaching full conversion at 20 min and 30 min, respectively, while the RE-CU-05 series shows a higher chemical stability than RE-CU-06 under the photooxidation conditions. The synthesis, characterization, photophysical properties, chemical stability, and photooxidation performance of these new RE-MOFs will be discussed
Digitization and Inequality: A Theoretical Model of Skill-Based Access
No full textDigital transactions are becoming an increasingly common medium of exchange in everyday life. However, their impact on income inequality remains insufficiently understood. The purpose of this paper is to investigate the relationship between the digitization of the economy and income inequality across heterogeneous agents differentiated by skill. We propose an income-digitization model that expresses income inequality as a function of two parameters: the level of digitization in the economy, characterized by internet penetration, and the effort cost associated with digital participation, which depends on agents’ education levels. A theoretical model is developed to examine how these factors interact to shape both intra- and inter-skill group income
distributions. Using the concept of Lorenz Dominance, the model compares pre- and post-digitization income to assess shifts in inequality, and we use simulation to understand the implications from the theoretical exercise. As digitization expands, the results suggest that inequality is reduced among the low-skilled group, but it increases between the low- and high-skilled groups. However, the threshold for digital participation declines, lowering the effective effort cost and enabling broader inclusion. This effect is further amplified by a targeted policy intervention in the form of a subsidy, which reduces the effort cost by between 7.89% and 11.32% across increasing levels of digitization. The results highlight the role of the monopoly government in reducing
exclusion for low-skilled agents
“Cold, Hunger, Fear, and Death” : The Silent Testimonies of Theresienstadt’s Youngest Witnesses
No full textMore than 150 000 Jews passed through the gates of the Theresienstadt Ghetto between 1941 and its liberation in 1945. Approximately 12,500 of them were children, only a few of whom survived. Some of these children left behind drawings and writings – fragments of memory resisting erasure. Focusing on one survivor’s autobiography and her haunting description of her “four closest companions” – Hunger, Cold, Fear, and Death – this study investigates how children in Theresienstadt represented their lived experiences through pictorial and narrative creative expressions. At the heart of this study is a collection of over 4,500 children’s drawings produced in the ghetto under the guidance of an art teacher in the children’s homes.
By exploring the presence and significance of these four companions, supplemented with excerpts from children’s diaries and memoirs of survivors, this study reveals how these themes were persistent emotional realities that shaped children’s understanding and portrayal of their world. This research also considers visual contrasts between pre-ghetto and ghetto life, such as the depiction of smoke rising from chimneys, and what the absence of such imagery might disclose about memory, loss, and rupture. Through the analysis of visual culture alongside historical and literary sources, children’s creative expressions emerge as silent testimonies of resilience, coping, and meaning making amid suffering. This research thus preserves the voices of children within Holocaust historiography and contributes to broader dialogues in Holocaust studies, memory studies, and the history of childhood
Design and Development of an Inception-Based Multiscale Algorithm for Single Image Super-Resolution
No full textThe field of single-image super-resolution (SISR) has made considerable progress with the emergence of deep convolutional neural networks, where residual learning techniques have played a crucial role in enhancing reconstruction quality. Among these methods, SwinIR, a transformer-based network, demonstrates remarkable performance by leveraging hierarchical self-attention mechanisms to effectively capture both fine-grained local structures and broader global contextual dependencies. However, enhancing image quality while maintaining computational efficiency remains a key challenge.
To address the limitations in capturing diverse spatial features without increasing architectural overhead, we propose EMS network, an enhanced multiscale SISR framework that draws inspiration from the inception module to refine feature extraction across multiple scales. Our network design adopts the underlying principle of parallel multi-scale feature extraction from the inception module, where several convolutional layers with different receptive fields operate to capture spatial features at multiple scales. Our method maintains the lightweight design of the network while broadening its receptive field, allowing it to surpass existing state-of-the-art methods in both efficiency and reconstruction quality. Quantitative and qualitative evaluations demonstrate that enhanced multiscale network consistently outperforms state-of-the-art SISR models on standard benchmark datasets, delivering improved visual quality and superior quantitative performance with minimal impact on computational complexity