• Consumer Response to Proactive and Reactive Corporate Social Responsibility (CSR) Contributions in the Environmental and Social Domains

  Siddique, Md. Zillur Rahman; Faculty of Business Programs

  Companies deploy proactive strategies to demonstrate their prosocial corporate social responsibility (CSR) engagement. Conversely, they may pursue reactive strategies to manage any social or environmental crises created by them. This study investigated the effects of proactive and reactive CSR, the moderating role of CSR domains, and the mediating role of consumer attribution on consumer responses. Using three experimental studies, this research found that proactive CSR leads to positive consumer attributions and favourable consumer responses compared to reactive CSR. Moreover, the CSR domain positively moderates the effects of CSR contribution on consumer responses and consumer attributions where proactive CSR in environmental domain than social domain generates more value- and strategic-driven motives and influence consumers’ favourable behavioural intentions. On the other hand, reactive CSR in the environmental domain diminishes favourable consumer reactions towards the firm and is perceived as less altruistic. Similarly, reactive CSR under social domain engenders egoistic motives. Furthermore, CSR domain moderates the mediation mechanism that indirectly links the CSR contribution and consumer response through consumer attributions. The study also discusses implications for practitioners and directions for future research.
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  Discourses of Social Inclusion in Sport and Recreation in Rural Ontario

  Nelson, Grace; Nelson, Grace; Applied Health Sciences Program

  The benefits and challenges of participating in sport and recreation as a new Canadian are well documented in the existing literature, however, they are typically considered in an urban context. More specifically, a gap exists regarding how sport and recreation practitioners and managers understand social inclusion work in sport and recreation and the impact these understandings may have on newcomer populations who are living in rural and other non-metropolitan communities. The purpose of this study was to gain a more in-depth understanding of how social inclusion is understood in both sport and recreation practice and policy. Further, I sought to critically examine discourses of Whiteness in programming and policy in rural settings. Therefore, in this research, I explored two questions: 1) How do sport and recreation practitioners and managers understand social inclusion in and through sport and recreation in their rural communities? and 2) How do discourses of community and inclusion impact the way sport and recreation practitioners and managers define and understand social inclusion? An instrumental case study methodology was used to explore these questions in a region of Northern Ontario (including Nipissing and Sudbury Districts) and both semi-structured interviews and document analysis were conducted to collect data. A critical discourse analysis (CDA) was used for this research which helped to highlight how discourse functions to construct and transmit knowledge, and the ways this organizes and maintains social institutions (Fairclough 2001; Mogashoa, 2014). I drew from Critical Whiteness theory (CWT) to better understand how discourses of Whiteness are produced and maintained in sport and recreation. The analysis identified three discourses related to social inclusion in sport and recreation: We’re all in this together; ‘They’ aren’t from here; and Whose responsibility is it?. This research highlights how discourses of colourblindness, “othering” of diverse populations, and ambiguity of responsibility for social inclusion work may inform practice and underpin systems of Whiteness in sport and recreation. Additionally, it is important to consider how policies, practices, and understandings of social inclusion work in sport and recreation settings are translated throughout and between organizations.  
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  Stepping away from pharmaceutical therapies: Exercise and supplementation with fermented red clover extract as alternative strategies to promote vascular health in postmenopausal women

  Wickham, Kate A.; Applied Health Sciences Program

  Cardiovascular disease is the leading cause of death worldwide. Both aging and menopause, associated with the cessation of endogenous estrogen production, are key factors that contribute to the development of cardiovascular disease in women. Over the last few decades, an interest in alternatives to pharmaceutical interventions for promoting and/or rescuing cardiovascular health in postmenopausal women has emerged, where both exercise and phytoestrogen supplementation have been deemed effective candidates. However, due to the paucity of intervention studies in postmenopausal women, knowledge gaps remain in these strategies that need to be elucidated in the context of vascular health. This dissertation aims to answer three main questions that will refine the scientific community’s understanding of alternative interventions for vascular health in postmenopausal women: (1) Can exercise training work synergistically with in-vitro dual anti-platelet therapy to improve platelet function, as determined by basal platelet reactivity and prostacyclin sensitivity (Chapter 4)? (2) Does the timing of the initiation of exercise training after menopause affect the degree of vascular adaptations and thrombotic risk profile (Chapters 5 and 6)? (3) Can short-term supplementation with the novel phytoestrogen fermented red clover extract improve markers of vascular inflammation (Chapter 7)? Together, the findings from this dissertation highlight that exercise and fermented red clover extract are effective alternative strategies to improving vascular health in postmenopausal women. Specifically, exercise training improves platelet function and sensitivity and can work synergistically with in-vitro dual anti-platelet therapy (Chapter 4). In addition, short-term supplementation with fermented red clover extract improves the vascular inflammatory profile in recently postmenopausal women (Chapter 7). However, the timing of exercise training after menopause may influence the magnitude of thrombogenic adaptations, as recently postmenopausal women experience more robust thrombogenic benefits than women who are a greater number of years postmenopausal (i.e., late postmenopausal women) (Chapter 5 and 6).
• The Effects of Heat and Cold on Cognitive Function and Endurance Capacity

  Wallace, Phillip Julian; Applied Health Sciences Program

  The maintenance of mental and physical function in hot and cold environments is more challenging compared to thermoneutral environments due to increases systemic physiological and psychological strain. The mechanism for impairments in both cognitive and physical function may be due to early perturbations in whole-body heat balance where the change in skin temperature (even before measurable changes in core temperature) impair performance, followed by greater impairments with changes in core temperature. However, the separate and combined effects of changes in skin and core temperature over a range of cognitive functions and exercise require further elucidation. Therefore, this dissertation tested cognitive function (psychomotor processing, working memory, and executive function) and endurance capacity (at 70% of peak power output) over a range of skin and core temperatures and thermal conditions. Chapter 4 investigates the effects of whole-body skin and core warming (hyperthermia) on cognitive function. In addition, the pharmacological drug, methylphenidate (20 mg, dopamine re-uptake inhibitor) was used as it may improve physiological and psychological strain during heat stress. Chapter 5 built upon Chapter 4 by testing the effects of whole-body skin and core cooling (mild hypothermia) on cognitive function. Chapter 6 extended the findings of Chapter 5 by testing the effects of whole-body skin and core cooling on endurance capacity, to potentially see a cognitive-physical performance interaction. Collectively, we found that neither changes in skin temperature (Range: ∆-6 to +4.5°C), without changes in core temperature, nor manipulation of core temperature (Range: ∆-0.8 to +1.5°C) significantly impaired cognitive function in hot or cold environments (Chapters 4 & 5). Furthermore, methylphenidate did not enhance cognitive function. Whereas, endurance capacity was significantly influenced by cold stress, where cooling the skin/outer shell impaired performance by 32%, while core cooling of ∆-0.5C and ∆-1.0C from baseline temperature further impaired performance by 61% and 71% respectively. There were no differences between the two core cooling conditions. Collectively, this research program demonstrates the capacity to maintain cognitive function, but not physical capacity under thermal strain. From a practical standpoint, interventions should focus to minimize cold strain to prevent declines in physical capacity under cold conditions.
• Exploring the Role of Internships in Personal and Professional Development

  Rutman, Jeremy; Applied Health Sciences Program

  Internships serve as an instrumental tool in many sport management students’ trajectory to becoming impactful employees and leaders in the sport industry. The purpose of this sequential mixed-methods study was to cultivate a better understanding of the development that occurs for students as they progress through an internship program, whether it be personal or professional. Internship outcomes related to personal and professional development alike occurred (e.g., personal maturing and growth, networking, and strategic reflection & change of mindset) and had an array of impacts on the outcomes of the study. Notably, contributing to the Experiential Learning Theory, the data outlined that no programmatic structures are in place to strategically build and/or assess students’ personal development; rather, personal development seemed to occur organically for certain participants in this study. Similarly, participants highlighted that soft skills were discussed as important by participants, but not necessarily explicitly addressed in their internship experience. The distinctive context and nature of COVID-19, embedded throughout these findings, provides a unique lens into the necessity of the abstract conceptualization and active experimentation phases of the Experiential Learning Cycle. The findings herein have important practical and theoretical implications for both sport management educators and internship supervisors in sport.
• Mobility-based Multi-layered Caching and Data Distribution in Vehicular Fog Computing

  Hassan, K M NAFIUL; Department of Computer Science

  Intelligent transportation systems provide valuable services to drivers and passengers, whereas vehicular networks enable fundamental underlying support through communication and data sharing. While edge and fog computing offers the benefits of providing support to access data closer to devices and applications, they come at the cost of requiring ongoing communication and computation. %Vehicular edge and fog computing became essential to access data almost instantaneously and perform computation closer to devices and applications; however, there is a high demand for continuous communication and computation. Therefore, caching data is a practical approach as it improves performance and enhances data availability. Moreover, the significant latency of the communication makes it prohibitive to fetch data from other sources. In the context discussed, caching data is a feasible option as it helps to increase performance and make data more readily accessible. Also, finding the desired data in the cache enables services besides improving performance. This study proposes a multi-layer caching mechanism that magnifies data availability while enhancing communication between the layers. The cache in the layers is distributive and updated on time based on the demand and criteria of the requests. We also distribute data using vehicular mobility by placing limited but significant data into the cache of the vehicle. These communication and data exchange types are standardized through policies in the proposed methodology. This cache management design is extensively analyzed using established frameworks and vehicular networks through simulated environments and visual constructions. Our simulation results indicate that the proposed method improves the performance of data availability and latency in vehicular fog computing. This approach can be applied to the diverse vehicle-to-everything use cases of the intelligent transportation system.
• Reinforcement Learning-based User-centric Handover Decision-making in 5G Vehicular Networks

  Murshed, Mubashir; Department of Computer Science

  The advancement of 5G technologies and Vehicular Networks open a new paradigm for Intelligent Transportation Systems (ITS) in safety and infotainment services in urban and highway scenarios. Connected vehicles are vital for enabling massive data sharing and supporting such services. Consequently, a stable connection is compulsory to transmit data across the network successfully. The new 5G technology introduces more bandwidth, stability, and reliability, but it faces a low communication range, suffering from more frequent handovers and connection drops. The shift from the base station-centric view to the user-centric view helps to cope with the smaller communication range and ultra-density of 5G networks. In this thesis, we propose a series of strategies to improve connection stability through efficient handover decision-making. First, a modified probabilistic approach, M-FiVH, aimed at reducing 5G handovers and enhancing network stability. Later, an adaptive learning approach employed Connectivity-oriented SARSA Reinforcement Learning (CO-SRL) for user-centric Virtual Cell (VC) management to enable efficient handover (HO) decisions. Following that, a user-centric Factor-distinct SARSA Reinforcement Learning (FD-SRL) approach combines time series data-oriented LSTM and adaptive SRL for VC and HO management by considering both historical and real-time data. The random direction of vehicular movement, high mobility, network load, uncertain road traffic situation, and signal strength from cellular transmission towers vary from time to time and cannot always be predicted. Our proposed approaches maintain stable connections by reducing the number of HOs by selecting the appropriate size of VCs and HO management. A series of improvements demonstrated through realistic simulations showed that M-FiVH, CO-SRL, and FD-SRL were successful in reducing the number of HOs and the average cumulative HO time. We provide an analysis and comparison of several approaches and demonstrate our proposed approaches perform better in terms of network connectivity.
• Time-Series Trend-Based Multi-Level Adaptive Execution Tracing

  Khan, Mohammed Adib; Department of Computer Science

  Troubleshooting system performance issues is a challenging task that requires a deep understanding of various factors that may impact system performance. This process involves analyzing trace logs from the kernel and user space using tools such as ftrace, strace, DTrace, or LTTng. However, pre-set tracing instrumentation can lead to missing important data where not enough components of the system include observability coverage. Also, having too much coverage may result in unnecessary noise in the data, making it extremely difficult to debug. This paper proposes an adaptive instrumentation technique for execution tracing, which dynamically makes decisions not only for which components to trace but also when to trace, thus reducing the risk of missing important data related to the performance problem and increasing the accuracy of debugging by reducing unwanted noises. Our preliminary results show that the proposed method is capable of handling tracing instrumentation dynamically for both kernel and application levels while maintaining a low overhead.
• Priority-Based Resource Allocation Model for Vehicular Fog Computing

  Ehsan, Mohaimin; Department of Computer Science

  Vehicle Fog Computing (VFC) provides opportunities to enhance a vehicle’s processing capability as well as support services and applications for intelligent transportation. Due to its low-latency characteristic, VFC has become progressively valuable and appropriate for delay-sensitive applications. Vehicles must overcome substantial obstacles to match the required services and carry out jobs effectively. Several methods have attempted cooperatively pooling idle vehicle resources, and just a few have looked at priority techniques. We concentrate on hierarchically allocating resources based on priorities. Priority is given to resource requests based on some attributes of the vehicle, such as deadlines, distances, and mobility considerations. Dynamic thresholds are determined using the fuzzy membership functions for each vehicular attribute. Prioritization is arranged using a priority queue to identify and assign managed resources under requests and availability. Our proposed method enables fulfilling QoS standards by reducing the length of time a service request spends in the system queue and ensuring high throughput through effective resource allocation. Simulated evaluations revealed decreased response times and total costs for servicing requests in large-scale urban scenarios.
• Determining Relationships Between Kinematic Sequencing and Baseball Pitch Velocity Using pitchAITM

  Bench, Ryan; Applied Health Sciences Program

  Professional baseball pitchers have consistently been increasing pitch velocity since 2008 (the first year of automated pitch tracking and classification at all 30 MLB stadiums) and increasing the number of pitches thrown over 95mph (Sullivan, 2019). Fastball velocity is a primary risk factor for elbow injuries as there is a general linear relationship with increased elbow torques (Aguinaldo & Chambers, 2009; Chalmers et al., 2016; Slowik et al., 2019). The kinematic sequence has been referred to as the order and magnitude of joint angular velocities during the pitch delivery and has been associated with pitch velocity and elbow torque (Nicholson et al., 2022a, 2022b; Scarborough, Leonard, et al., 2021). The purpose of the research was to identify kinematic sequence metrics associated with pitch velocity and use them to predict pitch velocity using pitchAITM (Dobos et al., 2022). A total of 80 pitchers (187.2 ± 8.2 cm, age 20.1 ± 3.3 years) ranging in skill level from high school to professional baseball participated in this study. Video for pitchAITM, player height and weight were collected at 2 baseball training facilities. Extracted pitchAITM data included the peak magnitudes and relative timings of pelvis rotation velocity, trunk rotation velocity, elbow extension velocity, and shoulder internal rotation velocity. Average pitch velocity in the data set was 85.3 ± 5.7 mph or 38.1 ± 2.5 m/s. Pitch velocity was predicted using both a multilinear regression, as well as a custom neural network model. The multilinear regression generated a significant prediction for pitch velocity with an R2 = 0.368 and p < 0.01. Pitcher weight (β = 0.535, p < 0.001), peak pelvis rotational velocity timing (β = -0.157, p = 0.001), peak elbow extension timing (β = 0.122, p = 0.006), and peak shoulder internal rotation timing (β = -0.113, p = 0.018), were significant contributors to the multilinear model. The neural network model significantly predicted velocity with an R2 = 0.372, p < 0.01. Actual and predicted velocity were not significantly different (p = 0.353). In conclusion, pitchAITM kinematic sequencing can predict pitch velocity using both a multilinear regression and custom neural network.
• The Effectiveness of Social Media Communications for Visitor Behaviour Management in Ontario's Parks and Protected Areas

  Foster, John S.; Applied Health Sciences Program

  Parks and protected areas in Ontario have long been bastions of conservation while also providing critical outdoor recreation opportunities for the health and well-being of the people. This was particularly evident during the early stages of the COVID-19 pandemic, where parks and protected areas agencies around the world experienced drastic increases in visitation as people sought opportunities to spend time in the natural world. However, the balance of environmental conservation and the provision of outdoor recreation opportunities are often seen as competing interests given the potential degradation that is associated with human use of these natural spaces. As a result, it is crucial for park managers and protected areas agencies to mitigate negative visitor behaviour issues as much as possible. Communications in their various formats (signage, in-person, etc.) have long been utilized by park agencies to share safety, regulatory, and interpretive information with park visitors. While the study of these communications is an underserved field of research, even less attention has been paid specifically to the utility of social media communications at delivering park agency messaging to visitors, especially in the context of addressing visitor behaviour issues using social media communications. This study will contribute to this identified research gap by exploring the experiences of both park visitors and park managers with respect to the effectiveness of social media communications for park visitor behaviour management. To do so, this study applied interpretive description methodology (Thorne, 2016) to support semi-structured interviews with park visitors and individuals who work for park agencies in Ontario in park management roles. 17 participants participated in the research project throughout the course of the data collection process. Conversations with participants revealed that the utility of social media communications for visitor behaviour management varies widely depending on the sophistication of the park agency’s social media strategy. Park visitors often expressed a desire for more specific, authentic, and discussion-oriented communications, while park managers frequently expressed a need to improve and increase the resources and logistics dedicated to social media communications to meet park visitor expectations.
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  A Framework for Meta-heuristic Parameter Performance Prediction Using Fitness Landscape Analysis and Machine Learning

  McDevitt, Liam; Department of Computer Science

  The behaviour of an optimization algorithm when attempting to solve a problem depends on the values assigned to its control parameters. For an algorithm to obtain desirable performance, its control parameter values must be chosen based on the current problem. Despite being necessary for optimal performance, selecting appropriate control parameter values is time-consuming, computationally expensive, and challenging. As the quantity of control parameters increases, so does the time complexity associated with searching for practical values, which often overshadows addressing the problem at hand, limiting the efficiency of an algorithm. As primarily recognized by the no free lunch theorem, there is no one-size-fits-all to problem-solving; hence from understanding a problem, a tailored approach can substantially help solve it. To predict the performance of control parameter configurations in unseen environments, this thesis crafts an intelligent generalizable framework leveraging machine learning classification and quantitative characteristics about the problem in question. The proposed parameter performance classifier (PPC) framework is extensively explored by training 84 high-accuracy classifiers comprised of multiple sampling methods, fitness types, and binning strategies. Furthermore, the novel framework is utilized in constructing a new parameter-free particle swarm optimization (PSO) variant called PPC-PSO that effectively eliminates the computational cost of parameter tuning, yields competitive performance amongst other leading methodologies across 99 benchmark functions, and is highly accessible to researchers and practitioners. The success of PPC-PSO shows excellent promise for the applicability of the PPC framework in making many more robust parameter-free meta-heuristic algorithms in the future with incredible generalization capabilities.
• Examining the Bilingual Mental Lexicon through Associative Priming

  Rollins, Matthew, Perham; Department of Psychology

  Research examining the associations between words in the monolingual versus bilingual mind has employed various models to examine differences in lexical organization, with varying degrees of success. The paradigms used have primarily been word association and semantic priming with a Lexical Decision Task (LDT). This thesis research has focused on the latter method, with an online data collection method using Testable. One distinction of this thesis research has been the types of semantic associations used for priming, namely syntagmatic and paradigmatic associations, which refer to either word context in a sentence, or word categories respectively. The control condition used from which facilitation effects were calculated was unrelated primes. In addition, a phonetic (or “clang”) priming condition was included as it was felt that it might tap into an important aspect of lexical organization for those who have English as a second language (L2). Recruitment was for native English-speaking monolinguals, native English-speaking bilinguals (who also speak a variety of other languages), and non-native English-speaking bilinguals (also from a range of language backgrounds) to participate. Results indicated that the paradigm was successful in gathering information about lexical associations in all three language groups. There was significant semantic facilitation across all language groups for both syntagmatic and paradigmatic associative primes, with these effects not differing from each other. Interestingly, only the L2 group showed significant facilitation from clang primes. Overall, the absolute priming effect was smaller than anticipated, despite reaching statistical reliability, suggesting possibilities to refine the display times of primes or targets. Other hypotheses concerned potential effects of participants’ context for L2 language learning and also attempts to address the main research question with the use of a classic word association task; however, both fell victim to the vagaries of online data collection. Nevertheless, the method and the software provide some hope for continued research in some aspects of the monolingual versus bilingual mental lexicon.  
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  Income Inequality, Distributive Justice, and Sustainable Development: Implications for Niagara Peninsula Aspiring Global Geopark

  Abbasov, Kamran; Environmental Sustainability Research Centre

  The rising inequalities across the world, including in Canada, present a challenge to achieving Sustainable Development Goals (SDGs). Under the auspices of UNESCO, supporting the implementation of SDGs is one of the main missions of geoparks. It has been shown that geoparks can foster the implementation of SDG 10 (reducing inequalities), but there is a dearth of studies specifically exploring the means and channels through which a geopark can help reduce income inequality. This study aims to fill that gap by exploring income inequality in the Niagara region through the lens of distributive justice with a focus on the role of Niagara Peninsula Aspiring Global Geopark (NPAGG) in reducing income inequality in Niagara. This study employs a qualitative research approach to collect data via 16 semi-structured interviews with the NPAGG board of directors, people who are advocating for poverty alleviation and reduction of inequalities in Niagara, and local tourism-related business owners. Thematic analysis was conducted on the collected data to explore the role of the NPAGG in addressing income inequality in the Niagara region. All the participants agreed that the income inequality in Niagara is unfair and needs to be addressed. The results of the thematic analysis show that in the pursuit of more equitable distribution in Niagara, the NPAGG can present economic benefits – with a direct yet incremental impact on income inequality – and societal benefits – with indirect yet necessary implications for addressing income inequality. There are two main limiting factors identified for the NPAGG’s role in battling income disparities: 1) it is not the primary objective of the NPAGG, and 2) the problem of income inequality is much bigger than the NPAGG. Moreover, inflation, negative environmental impacts, and dependence on tourism were identified as minor risks associated with the NPAGG development. Although the findings of this study may not be generalized to other geoparks around the world, they offer understanding of what to expect from geoparks in addressing income disparities.
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  A Parent's Autoethnography: Examining My Experiences and Identity as Parent, Educator, and Researcher While Teaching Literacy to My Adolescent Sons Who Have Autism and Use Augmentative and Alternative Communication

  Kavsak, Heather; Department of Graduate and Undergraduate Studies in Education

  This autoethnography was completed from my unique perspective as a mother to two adolescent sons with autism spectrum disorder (ASD) who have complex communication needs and use augmentative and alternative communication (AAC) to communicate. Although literacy is a human right (Ontario Human Rights Commission, 2022a), it often has been overlooked in my sons’ self-contained classrooms in high school. As my sons’ parent and educator, I gathered my reflections, observations, descriptions, journals, lesson plans, and artifacts to examine the experiences I encountered in developing their literacy. Initially, I conducted a pilot project based on Erickson and Koppenhaver’s (2007) Children With Disabilities: Reading and Writing the Four Blocks® Way, the results of which guided my planning in teaching literacy with an adaptation of the more recent Comprehensive Literacy for All: Teaching Students With Significant Disabilities to Read and Write (Erickson & Koppenhaver, 2020). I coded by hand each line of the collected data to extract categories and then streamline these into the meaningful themes to respond to my two research questions: (a) What are the experiences of a parent educator who has been teaching literacy awareness and skills to her adolescent sons who both have autism and use AAC devices? (b) Does the experience shape her identity as a parent, educator, and researcher? Thematic findings pertaining to the first question revealed experiences related to planning and questioning and my own transformational learning and mindshift. Thematic findings related to the second question include: Parental concerns; Educator: advocating and imposter syndrome; Researcher: Lesson planning and questioning; and Transformational learning and mindshift. Findings are discussed in light of the literature on experiences of parents as educators of children with exceptionalities. The study also presents implications for theory, practice, and research, as well as limitations and future directions.
• Enhancing Lexical Sentiment Analysis using LASSO Style Regularization

  Blanchard, Jeremy; Department of Mathematics

  In the current information age where expressing one’s opinions online requires but a few button presses, there is great interest in analyzing and predicting such emotional expression. Sentiment analysis is described as the study of how to quantify and predict such emotional expression by applying various analytical methods. This realm of study can broadly be separated into two domains: those which quantify sentiment using sets of features determined by humans, and approaches that utilize machine learning. An issue with the later approaches being that the features which describe sentiment within text are challenging to interpret. By combining VADER which is short for Valence Aware Dictionary for sEntiment Reasoning; a lexicon model with machine learning tools (simulated annealing) and k-fold cross validation we can improve the performance of VADER within and across context. To validate this modified VADER algorithm we contribute to the literature of sentiment analysis by sharing a dataset sourced from Steam; an online video game platform. The benefits of using Steam for training purposes is that it contains several unique properties from both social media and online web retailers such as Amazon. The results obtained from applying this modified VADER algorithm indicate that parameters need to be re-trained for each dataset/context. Furthermore that using statistical learning tools to estimate these parameters improves the performance of VADER within and across context. As an addendum we provide a general overview of the current state of sentiment analysis and apply BERT a Transformer-based neural network model to the collected Steam dataset. These results were then compared to both base VADER and modified VADER.
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  Analysis of Parkinson's Disease Gait using Computational Intelligence

  mohamad beigi, omid; Department of Computer Science

  Millions of individuals throughout the world are living with Parkinson’s disease (PD), a neurodegenerative condition whose symptoms are difficult to differentiate from those of other disorders. Freezing of gait (FOG) is one of the signs of Parkinson’s disease that have been utilized as the main diagnostic factor. Bradykinesia, tremors, depression, hallucinations, cognitive impairment, and falls are all common symptoms of Parkinson’s disease (PD). This research uses a dataset that captures data on individuals with PD who suffer from freezing of gait. This dataset includes data for medication in both the “On” and “Off” stages (denoting whether patients have taken their medicines or not). The dataset is comprised of four separate experiments, which are referred to as Voluntary Stop, Timed Up and Go (TUG), Simple Motor Task, and Dual Motor and Cognitive Task. Each of these tests has been carried out over a total of three separate attempts (trials) to verify that they are both reliable and accurate. The dataset was used for four significant challenges. The first challenge is to differentiate between people with Parkinson’s disease and healthy volunteers, and the second task is to evaluate effectiveness of medicines on the patients. The third task is to detect episodes of FOG in each individual, and the last task is to predict the FOG episode at the time of occurrence. For the last task, the author proposed. a new framework to make real-time predictions for detecting FOG, in which the results demonstrated the effectiveness of the approach. It is worth mentioning that techniques from many classifiers have been combined in order to reduce the likelihood of being biased toward a single approach. Multilayer Perceptron, K-Nearest Neighbors, random Forest, and Decision Tree Classifier all produced the best results when applied to the first three tasks with an accuracy of more than 90% amongst the classifiers that were investigated.
• An Assessment of Best Practices of Corporate Sustainability Strategies in Canadian SMEs

  Bute-Seaton, Kelly; Environmental Sustainability Research Centre

  Humanity is faced with existential threats of our own doing that require our collective action. Small-medium-sized enterprises (SMEs) by virtue of their large numbers and prevalence in society have the potential to contribute to economic, social, and environmental development and play a critical role in Sustainability at a global level. This can be accomplished through their business practices, systems, policies, and interactions. The purpose of this study is to explore the corporate sustainability practices of SMEs ranked highly for their involvement in Sustainability through an online survey with key representatives of seventeen (17) SMEs. The findings demonstrated that many companies are willing to play a greater role in CSR/ Corporate Sustainability but are stymied by the lack of resources, applicable frameworks, and an enabling environment. These results have valuable implications for SMEs, academia, Government, NGOs, business associations, and the private sector.
• Intimate Deathscapes: Examining Alternative Discourses of the Dead Body and Death Care Spaces

  Giesbrecht, Jennica; Department of Geography

  Over the last two centuries Western death care has undergone a gradual process of defeminization, professionalization, and medicalization. It has also grown into a multi-billion-dollar industry and is now facing criticism for practices that are financially exploitive, environmentally harmful, and contribute to the invisibilization of death. Over the last decade, alternative understandings of death and death care practices have begun to emerge in response to these criticisms. Some of these alternative understandings come from death care workers who espouse the benefits of engaging with death. In this thesis I examine the spaces of the dead body and death care spaces, which I refer to as intimate deathscapes. To consider the formation of subjectivities and knowledge production within intimate deathscapes, this thesis examines three autobiographies from death care workers (Doughty, 2014; Nadle, 2006; Wilde, 2017). The authors make compelling claims about the positive influence that can come from more engagement with death, which differ significantly from dominant discourses that pathologize death and cloak it in negativity and fear. Alternatively, they propose embracing mortality as a way of improving one’s life. I conclude that their material engagement with dead bodies, as represented in these texts, effects an epistemic shift in relation to death. Employing a material feminist framework, I argue that the spatiality and materiality of deathscapes influences the formation of subjectivities, and it is the relational and emergent subjectivities of the living and agencies of the dead that together produce an alternative knowledge about death, and consequently life. This knowledge contests the pathologization of the dead body and instead considers the potentially beneficial effects of more engagement with death. Therefore, in arguing that deathscapes are spaces from which these alternative death epistemologies can emerge, I echo challenges to dominant death care practices and support emerging discourses that propose more robust communication about death and call for changes to death care as a means toward more meaningful engagement in intimate deathscapes.
• Distributed MAP-Elites and its Application in Evolutionary Design

  Hon, Derek; Department of Computer Science

  Quality-Diversity search is the process of finding diverse solutions within the search space which do not sacrifice performance. MAP-Elites is a quality-diversity algorithm which measures n phenotypes/behaviours of a solution and places it into an $n$-dimensional hypercube based off its phenotype values. This thesis proposes an approach to addressing MAP-Elites' problem of exponential growth of hypercubes. The exponential growth of evaluation and computational time as the phenotypes/behaviours grow is potentially worse for optimization performance. The exponential growth in individuals results in the user being given too many candidate solutions at the end of processing. Therefore, MAP-Elites highlights diversity, but with the exponential growth, the said diversity is arguably impractical. This research proposes an enhancement to MAP-Elites with Distributed island-model evolution. This will introduce a linear growth in population as well as a reasonable number of candidate solutions to consider. Each island consists of a two dimensional MAP which allows for a realistic analysis and visualization of these individuals. Since the system increases on a linear scale, and MAP-Elites on an exponential scale, high-dimensional problems will show an even greater decrease in total candidate solution counts, which aids in the realistic analysis of a run. This system will then be tested on procedural texture generation with multiple computer vision fitness functions. This Distributed MAP-Elites algorithm was tested against vanilla GP, island-model evolution, and traditional MAP-Elites on multiple fitness functions and target images. The proposed algorithm was found, at the very minimum, to be competitive in fitness to the other algorithms and in some cases outperformed them. On top of this performance, when visually observing the best solutions, the algorithm was found to have been able to produce visually interesting textures.

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