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Reinforcement Learning-based User-centric Handover Decision-making in 5G Vehicular Networks
Get PDFThe 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
Bias, Barriers, and Discrimination: Treatment of Indigenous Peoples in Wellness Courts
Get PDFMajor Research Paper (MRP) focused on Indigenous knowledge systems compared to Wellness Courts, engaging a critical literature review that integrates insights from professional practice experiences as a Registered Social Worker. As a result, reflexivity was used as a key method in the research and facilitated an in-depth analysis of current literature. This MRP is positioned to contribute to understanding the impact of Wellness Courts concerning the needs and goals of Indigenous communities
Time-Series Trend-Based Multi-Level Adaptive Execution Tracing
Get PDFTroubleshooting 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
Can we Speak Sustainability into Existence? Shareholder Engagement and Corporate Innovation Strategy
Get PDFThe Voice strategy applied to engagements on ESG issues might affect firms’ reporting decisions and symbolic ESG performance, but what about real decisions? In this study, we investigate the effect of environmental shareholder activism on target firms’ innovation strategies, particularly their green and dirty innovation output. We posit that the relationship is theoretically ambiguous and can be driven either by better monitoring and higher scrutiny by shareholders and stakeholders or by shorttermism, legitimacy gains, and career concerns. We utilize the Direct Acyclic Graph (DAG) to construct our empirical strategy. We also use a hurdle model coupled with propensity score matching and a difference in difference specification in an attempt to estimate an unbiased average treatment effect for the treated (ATT). The results of the first stage show no evidence of a relationship between shareholder environmental activism through shareholder proposals and a firm’s likelihood of engaging in either type of innovation. In the second stage, we find weak evidence for a negative relationship between environmental shareholder activism and dirty innovation. The estimated economic magnitude of this potentially causal relationship ranges from a 25% to a 53% reduction in dirty innovation output among target firms. However, we are unable to obtain reliable estimates for the relationship between environmental shareholder activism and green innovation. Through a cross-sectional analysis, we further show that firms subject to a higher regulatory environmental scrutiny through the TRI reporting requirements drive the negative relationship between environmental shareholder activism and dirty innovation, and we also find weak evidence for the superior ability of institutional activist to influence firms’ dirty innovation output. Our findings contribute to the voice versus exit debate by showing that voice can be effective in curbing firms’ negative environmental externalities but might not result in the provision of public goods. We inform the debate on shareholder proposal rules by showing that environmental shareholder proposals, often excluded by SEC rule 14a-8, have the potential to promote sustainability in the private sector
Convergence Analysis of Heterogeneous Decision-making Populations Under the Coordinating Best-response and Imitation Update Rules
Get PDFThis thesis emphasis is on coordination games.
In a coordination game, selecting the same strategy or decision as the opponent is mutually beneficial for both parties.
We studied the problem of equilibrium convergence in such games in both discrete and continuous (time) cases.
In the first Chapter, we provide a brief introduction to the field of game theory. We discuss different categories of agents based on their levels of rationality and decision-making strategies, along with a variety of games. Additionally, we address important issues and challenges within this field.
The second Chapter of this work is dedicated to a heterogeneous mixed population of imitators and best-responders.
In this model, agents’ update rules are assumed to be discrete functions of time.
Imitators refer to agents who simply replicate the strategy of another agent with the highest payoff, while best-responders pick the strategies that maximise their individual outcomes.
Suggesting the concept of ’sections’--a consecutive sequence of agents with similar strategies– helped us in establishing convergence to an equilibrium state.
This convergence was demonstrated under any arbitrary asynchronous activation sequence within a linear network.
The proof was then extended to networks with ring, starike, and sparse-tree structures.
However, the question of equilibrium convergence for other network structures remains an open challenge.
In the third Chapter, we examined a large well-mixed population of imitators within a coordination context.
Our analysis is grounded in the assumption that imitation here is driven by dissatisfaction. Equivalently, agents with lower payoffs are more dissatisfied and have more tendency to change and imitate higher earners within the population.
The analysis reveals the presence of three fixed points, of which two are stable and one is a saddle point. The stable manifold of the unstable fixed point is also calculated. Additionally, It is demonstrated that starting from any initial state, the population eventually converges towards one of these introduced fixed points
Diversifying Emergent Behaviours with Age-Layered MAP-Elites
Get PDFEmergent behaviour can arise unexpectedly as a by-product of the complex interactions of an autonomous system, and with the increasing desire for such systems, emergent behaviour has become an important area of interest for AI research. One aspect of this research is in searching for a diverse set of emergent behaviours which not only provides a useful tool for finding unwanted emergent behaviour, but also in finding interesting emergent behaviour. The multi-dimensional archive of phenotypic elites (MAP-Elites) algorithm is a popular evolutionary algorithm which returns a highly diverse set of elite solutions at the end of a run. The population is separated into a grid-like feature space defined by a set of behaviour dimensions specified by the user where each cell of the grid corresponds to a unique behaviour combination. The algorithm is conceptually simple and effective at producing high-quality, diverse solutions, but it comes with a major limitation on its exploratory capabilities. With each additional behaviour, the set of solutions grows exponentially, making high-dimensional feature spaces infeasible. This thesis proposes an option for increasing behaviours with a novel Age-Layered MAP-Elites (ALME) algorithm where the population is separated into age layers and each layer has its own feature space. By using different behaviours in the different layers, the population migrates up through the layers experiencing selective pressure towards different behaviours. This algorithm is applied to a simulated intelligent agent environment to observe interesting emergent behaviours. It is observed that ALME is capable of producing a set of solutions with diversity in all behaviour dimensions while keeping the final population size low. It is also observed that ALME is capable of filling its top layer feature space more consistently than MAP-Elites with the same behaviour dimensions
The Risk of Greenwashing in Corporate Social Responsibility Communications
Get PDFThere is a growing expectation from consumers that companies recognize the environmental impact of their businesses and engage in corporate social responsibility (CSR) initiatives. While the demand for CSR has increased, so has the prevalence of greenwashing, which has caused consumers to be more skeptical about a company’s motives when CSR is promoted. Marketing practitioners are faced with the challenge of balancing the demand for corporate responsibility with the skepticism of greenwashing. This study consists of a survey of 22 marketing practitioners in Canada to explore their experiences when developing CSR-related communications and how they establish trust with audiences to reduce the perception of greenwashing. The results illustrate that practitioners manage the risk of greenwashing by developing messages that do not self-promote, showcasing concrete action and evidence to support claims, relying on positive marketing appeals such as pride and compassion, and tailoring messages based on the audience and industry a company belongs to
Pelham LACAC (Local Architectural Conservation Advisory Committee) fonds, 1861-2001, n.d.
Get PDFLocal Architectural Conservation Advisory Committees (LACAC) were established around the time the Ontario Heritage Act was enacted in 1974. The committees were appointed by Municipal Council to advise on heritage matters within their communities. Over the years, the work of these committees has expanded to include cultural and natural heritage as well as buildings. To better reflect the scope of their work, LACAC became known as Municipal Heritage Committees. LACAC volunteers worked in separate committees within different areas of Niagara, including St. Catharines, Thorold, Niagara Falls, and Pelham.Fonds contains material relating to the work of the Pelham LACAC (Local Architectural Conservation Advisory Committee). Much of the material concerns the Comfort Maple tree in Pelham. Some other material about historic buildings in Pelham is also included. Material was kept in its original order and includes meeting minutes, correspondence, news clippings, reports, and maps
Off track or on point? Side comments in focus groups with teens
Get PDFSide comments and conversations in focus groups can pose challenges for facilitators. Rather than seeing side comments as problematic behavior or “failed” data, we argue that they can add to and deepen analyses. Drawing on focus group data with grade nine students from a study on early work, in this methodological paper we discuss three patterns. First, side comments have highlighted where participants required clarification, and illustrated their views and questions about the research process. Second, side comments added new data to our analysis, including personal reflections, connections to others’ comments, and information about participants’ uncertainties about the research topics. Third, these comments offered insight into peer relations and dynamics, including participants’ reflections on age, and how they deployed gender relations in their discussions. Provided that their use fits within established ethical protocols, we argue that there is a place for attention to side comments, especially in focus group research with young people where adult-teen hierarchies and peer dynamics might lead young people to engage more with peers than directly respond to researchers’ questions
A Study of Soccer Space Gain in Pass Sequences using Logistic Regression
Get PDFSome pass sequences open up more space on the pitch than others. Several studies about space gain in soccer have been performed in the past, but the relationship between space gain and the ability to score a goal has not been established yet. This research aims to predict goal occurrence by using total space gain for each pass sequence as the explanatory variable in logistic regression. Combining event and tracking data from the 2019 regular season of Chinese Super League (CSL), space quality can be calculated. We implemented space quality calculation from for 237 matches in the 2019 CSL dataset. Space quality is defined as the product of likelihoods that a team can gain control at a given location and time and the defending team can impede scoring attempts. The research demonstrated that for every unit the total space gain increased in a given pass sequence, the scoring odds increased by 23%. This finding showcases that pass sequences that create space are more likely to help in scoring, which is consistent with real-life soccer events. Combining the space occupation gain and probability of scoring a goal in every pass sequence, a team could make an informed decision of how they should position each player in a given scenario