Browsing by Author "Brennan, Robert"

Now showing 1 - 11 of 11
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    Artificial intelligence and academic integrity: The ethics of teaching and learning with algorithmic writing technologies
    (2023-01-25) Eaton, Sarah Elaine; Brennan, Robert; Wiens, Jason; McDermott, Brenda
    The higher education landscape is changing rapidly, with artificial intelligence tools being increasingly available to students, as well as the general public. In this session, we present basic information about artificial intelligence and algorithmic writing technologies such as GPT-3 and other tools. We will contemplate the broader impact of artificial intelligence on teaching, learning, assessment, and academic integrity. Debating whether the use of artificial might or might not constitute academic misconduct is an overly reductionist and polarizing approach to the debate. Our value proposition is that artificial intelligence is already here and as educators we have a responsibility to ensure we are taking an ethical approach about how it can be used for teaching, learning, and assessment. We discuss how artificial intelligence tools can be used to support ethical and equitable approaches to student success. Keywords: artificial intelligence, academic integrity, academic misconduct, plagiarism, GPT-3, ChatGPT, large language models (LLM), algorithmic writing, transdisciplinary, transdisciplinarity Cite this presentation as: Eaton, S. E., Brennan, R., Wiens, J., & McDermott, B. (2023, January 25). Artificial intelligence and academic integrity: The ethics of teaching and learning with algorithmic writing technologies Invited talk for the Webinar Series organized by the Faculty Merit Committee (FMC) Learning Development Team, Bournemouth University, UK.
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    Critical Pedagogical Interventions in Engineering: Deconstructing Hierarchical Dualisms to Expand the Narratives of Engineering Education
    (2024-01-12) Paul, Robyn Mae; Brennan, Robert; Behjat, Laleh; Eggermont, Marjan; Black, Kerry; Sun, Qiao; Sengupta, Pratim; Lord, Susan
    Engineering in the western world is often framed as neutral or apolitical, meaning engineering education trains engineers to take little responsibility for perpetuating society’s biases through our technologies (such as racism, colonialism, and environmental degradation). In this thesis, I argue that as problem solvers and critical thinkers involved in the world’s biggest challenges, it is our ethical responsibility to unmask the hidden belief systems and dominant narratives that currently drive the engineering sector. Within our society, dualisms are embedded across our value systems, such as the dualisms of woman-man, emotion-reason, nature-culture, and social-technical. These dualisms exist as opposites, exclusive, and in a value-hierarchy (i.e. man-reason-culture-technical are typically viewed in exclusive opposition and valued higher than woman-emotion-nature-social). This thesis uses the hierarchical dualisms pedagogical framework to bring light to the normative cultures of engineering education and aims to support engineering education communities in increasing their critical consciousness and becoming aware of dominant value systems. Thus, my primary research question is: How do we design practices that unmask the hierarchical dualisms to build expanded narratives of engineering and engineering education? I answer this question by (1) outlining a framework of hierarchical dualisms and dominant narratives including illustrative case studies; (2) summarizing two pedagogical innovations I designed and implemented to unmask different hierarchical dualisms; and (3) analyzing my own writing for dominant narratives through a discourse analysis. Throughout, this thesis takes a non-traditional research approach to align my methodology with the epistemological assumptions of the research paradigm. I leverage dialogicity, relationality, and storytelling methodologies to describe my journey of doing paradigm shifting work in the field of engineering education. Overall, this thesis found that through increasing critical consciousness, broadening our systems thinking, engaging in interdisciplinary dialogue, being willing to transcend engineering boundaries, and imagining radical futures we can create momentum for emergent change that will foster liberatory education. As educators, students’ four years of undergraduate engineering in academia are our great opportunity to radically transform engineering students’ way of thinking about technology and design, and give them the skills and tools to radically transform the purpose of engineering.
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    Decentralized Scheduling Using The Multi-Agent System Approach For Smart Manufacturing Systems: Investigation And Design
    (2023-09-20) Ebufegha, Akposeiyifa Joseph; Li, Simon; Brennan, Robert; Lee, Jihyun
    The advent of industry 4.0 has resulted in increased availability, velocity, and volume of data as well as increased data processing capabilities. There is a need to determine how best to incorporate these advancements to improve the performance of manufacturing systems. The purpose of this research is to present a solution for incorporating industry 4.0 into manufacturing systems. It will focus on how such a system would operate, how to select resources for the system, and how to configure the system. Our proposed solution is a smart manufacturing system that operates as a self-coordinating system. It utilizes a multi-agent system (MAS) approach, where individual entities within the system have autonomy to make dynamic scheduling decisions in real-time. This solution was shown to outperform alternative scheduling strategies (right shifting and dispatching priority rule) in manufacturing environments subject to uncertainty in our simulation experiments. The second phase of our research focused on system design. This phase involved developing models for two problems: (1) resource selection, and (2) layout configuration. Both models developed use simulation-based optimization. We first present a model for determining machine resources using a genetic algorithm (GA). This model yielded results comparable to an exhaustive search whilst significantly reducing the number of required experiments to find the solution. To address layout configuration, we developed a model that combines hierarchical clustering and GA. Our numerical experiments demonstrated that the hybrid layouts derived from the model result in shorter and less variable order completion times compared to alternative layout configurations. Overall, our research showed that MAS-based scheduling can outperform alternative dynamic scheduling approaches in manufacturing environments subject to uncertainty. We also show that this performance can further be improved through optimal resource selection and layout design.
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    Development of a Real-time Performance Measurement System for Sprint Starts
    (2017) Iyer, Parth; Brennan, Robert; Goldsmith, Peter; Ronsky, Janet Lenore; Herzog, Walter
    This thesis is an expansion of a Capstone Project where a set of portable sprint starting blocks that can be used for training was developed. For this thesis, two piezo-electric sensors were implemented in the blocks that transmitted data from each of the sprinter’s feet to a micro-controller. The sensors, after a series of impact hammer tests, offered a cost-efficient means of collecting valuable telemetric data during a sprint start, and crucially, were non-intrusive. Majority of the athletes demonstrated a consistent three-peak-force pattern in the data collected which was statistically correlated to qualitative performance scores given by a coach evaluating the start. The correlation helped develop a fuzzy method that estimated a performance score for sprint starts and detected false starts. The need to validate this method also helped produce a definitive coach’s sprint start evaluation checklist from the National Coaching Certification Program.
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    Digital Twins for Distributed Control Systems in IEC 61499
    (2023-05-08) Lesage, Jonathan Lee Vivian; Brennan, Robert; Lee, Jihyun; Carriere, Jay
    Digital twins are at the centre of smart manufacturing and production in Industry 4.0. Literature surrounding digital twins demonstrates them to be key in optimizing production systems, monitoring system performance, detecting and predicting faults, intervening in production operations if needed, and even designing new manufacturing systems. They achieve these feats by applying a high-fidelity model of a device built from the understood physics in combination with all available and applicable sensor data, and by establishing a bidirectional communication pathway that allows the digital twin to receive data and send signals. Whatever the goal of a specific digital twin, it typically achieves it by using its model to simulate the physical system in some form. While the features described here are common amongst nearly all digital twins, the concept becomes less clear once the literature is reviewed more thoroughly. Not only do the features of a digital twin vary with different authors, but the method of constructing them varies even further. This issue is noted in research on the topic and acts to bar the application of digital twins in a widespread manner. This thesis aims to resolve this issue for production systems managed through distributed control systems. An architecture for digital twins that makes use of a high level programming language, in this case MATLAB, in combination with IEC61499 function blocks is proposed. The architecture produces a twin capable of the key functions necessary for it to be useful in a production system, such as model construction and system monitoring and simulation, and produces a bi-directional communication pathway which allows it to interact with the device and the remaining control system. The digital twin architecture’s functionality is demonstrated and evaluated through a series of tests. Digital twins are a key element to establishing a distributed intelligent sensing and control system, that is a distributed control system which can self manage and operate intelligently and autonomously. This thesis explains how this may be achieved in the IEC61499 standard, and how the digital twin architecture produced here supports this objective.
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    Distributed autonomous systems to track mobile nodes in industrial wireless sensor networks
    (2014-05-20) Gholami, Mohammad; Brennan, Robert
    With an ever-increasing trend in automating industrial processes and systems, and with a need to collect and manage information and sensory data in an economic, secure, reliable, and real-time fashion, wireless sensor networks have arisen as one promising solution. One of the imperative problems in the realm of wireless sensor networks is the problem of wireless sensors localization. Although much research has been conducted in this area, many of the proposed approaches produce unsatisfactory results when exposed to dynamic and noisy conditions of a manufacturing environment. This research, first, presents a robust solution, based on artificial neural networks, to tackle the problem of mobile node tracking in industrial wireless sensor networks. The proposed technique is tested on a simulation model, and the results obtained are validated with a physical small-scale wireless sensor network. A sensitivity analysis follows the simulation and physical model studies to investigate the impact of a set of ambient factors and wireless sensor network parameters on the proposed technique. Much of the studies in the literature of the mobile node tracking merely focus on the accuracy of the localization technique. Nevertheless, to design a successful tracking technique for industrial wireless sensor networks requires one to address many more concerns. In industrial wireless sensor networks, where hundreds to thousands of wireless nodes are deployed, resource management, response time, load distribution, reconfigurability, and adaptability of a tracking system become of paramount importance. Thus, this research presents three tracking systems to position mobile nodes in industrial wireless sensor networks in a soft real-time fashion. Each tracking system employs a unique wireless sensor network topology, namely static clusters, dynamic clusters and ad hoc networks of wireless nodes. Each tracking topology is, in turn, governed by a unique multi-agent system. Subsequently, a comprehensive experimentation based on statistical designs is performed to analyze and compare the performance and efficiency of the proposed tracking systems with respect to a set of formulated metrics. The results obtained illustrate that while ad hoc networks exhibit higher performance, the static and dynamic clusters excel in efficiency related metrics.
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    Multi-Agent Autonomous Intersection Management Systems
    (2021-06-11) Baradaran Amini, Sama; Brennan, Robert; Behjat, Laleh; Li, Simon
    With the advancements in the field of autonomous driving, it is important to plan safe and efficient ways to regulate traffic once self-driving vehicles actually take the road. One of the most important points in traffic regulation is the intersection management system as it is the single point with highest congestion and collision rates. Most of the previous research that has been performed in this field, suggest a single form of autonomous intersection management system, and compare results with the conventional light-signal system. Through these results, it is clear that the light-signal controlled intersections have no place in the world of autonomous driving. Therefore, in this research the effort has been made to evaluate multiple autonomous multi-agent intersection management systems and arrive at the most feasible and efficient model by comparing them to each other especially with a focus on agent communication metrics. This thesis presents three separate models for autonomous multi-agent intersection management, and moves towards evaluating performance of each system, separately, and compared to each other. The two centralized multi-agent systems provide a more secure and reliable method as they can drop collision rates to zero. However, a decentralized system can regulate traffic faster while requiring a more powerful IT infrastructure to handle large number of agent communications in the system.
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    Opportunities for and Barriers to Innovation in Engineering Education
    (2019-01-04) Meikleham, Alexandra; Hugo, Ronald J; Brennan, Robert; Johnston, Kimberly
    The 21st Century has brought both tremendous promise and challenge for engineers. The need for sustainable development and growing pressures from automation are some of the societal challenges facing tomorrow’s engineering graduates. Educational institutions must ensure students possess competencies in professional skills, such as adaptability, critical thinking and creativity to thrive in today’s rapidly evolving ecosystem. Continuous improvement in teaching techniques and content will be required to ensure students are prepared for life beyond graduation. Technology-mediated course delivery, blended learning, and project-based learning are promising approaches to work lateral thinking and professional skills into the curriculum; but no new solution comes without drawbacks. It is critical that ongoing research be conducted and documented into the effectiveness of interventions so that informed decisions on course and program design can be made. This work presents findings and experiences of implementing a technical project-based, blended fluid mechanics course; analyzes factors that affected professional skills development indicated by twelve Graduate Attributes. Project-based and blended learning were found to be effective in developing professional skills, however several institutional barriers were identified to the scalability of these approaches. Two self-efficacy surveys were assessed for their reliability, and opportunities were identified for future improvements to be made on several survey questions. Opportunities for the development of professional modules on ethics and equity, professionalism, and lifelong learning were identified. End of term student surveys revealed that as student-centred approaches to teaching and learning increased, student perception of teaching quality decreased and workload increased, indicating a potential barrier to achieving buy-in from tenure-track instructors who rely on student end of term survey results for promotion. Teaching assistant training, resource allocation, risk management, and institutional memory were identified as critical areas requiring interventions for project-based learning to be sustained within the system. This work can be utilized to inform discussions on local program design within the University of Calgary, but the insights and ideas presented are relevant for instructors, institutions, and international initiatives looking to facilitate sustainable educational change across the post-secondary system as well.
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    Production Planning and Control for Flexible Interim Product Manufacturing in One-of-a-Kind Production
    (2016) Ying, Mei; Brennan, Robert
    One-of-a-kind production (OKP) is generally complex flexible production which is characterized by discrete and non-numerical production decomposition, product design uncertainty and changes in resource availability. The old production management and control system, theory and methods do not handle this situation well because these technologies are developed with a view to time-invariant or static production state in the traditional large batch size manufacturing companies. Considering the manufacturing project (i.e. production planning and execution process) of OKPs as the main line of research, and by clarifying the optimal control and operational management of interim product production from a viewpoint of control system, we aim at analyzing the relationship between the control system actions and the crucial production indices that characterize working time expenditure, man hour cost and workforce consumption; and developing a closed-loop dynamic production cost control and optimization system of interim products based on working hours and manpower for OKP. The research involves the following aspects: First: A method for workforce allocation and working time optimization problem with discrete and non-numerical constraints in OKP. With a top-down refinement method to specialize the product design and production decomposition in OKP, we suggest three unit task structures. For the typical double-level-nested parallel structure, according to analysis of complex industrial scenarios, a discrete-nested-set DP (dynamic programming) is presented to solve the workforce allocation and working time optimization problem. Second: The optimal control methods based on MLHPP (the multilevel hierarchical PERT-Petri net) are proposed to analyze dynamic interim production cost control and optimization under different workforce allocation and working time scenarios in a closed-loop control system. Third: Entropy-weighted ANP fuzzy comprehensive evaluation of interim product production processes in OKP. OKP interim product production has the nature of multi-criteria production. To optimize the production processes influenced by complex factors, we establish an influence factor system and present a method that combines subjective and objective weights based on the entropy and an analytic network process (ANP).
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    Quantitative and Qualitative Evaluation of a Novel Remote Actuation System versus Traditional Designs
    (2022-09-15) Irwin, Alexander; Goldsmith, Peter; Brennan, Robert; Xue, Deyi; Shrive, Nigel; Goldsmith, Peter; Brennan, Robert
    Remote actuation systems (RAS) are used in robot design to relocate actuators away from joints. Several such RAS have been investigated by researchers, including pneumatic and hydraulic cylinders, cable-pulley systems, and flexible Bowden cables. However, testing of these systems is often not comparative and is focused on specific metrics without consideration of overall robot performance. The purpose of this research is to compare the performance of a novel RAS called the Fluid-cable transmission (FCT) with traditional RAS consisting of push-pull cables and conventional hydraulic and pneumatic cylinders. The static friction and stiffness of these RAS are compared for a range of bend angles, fluids, and operating pressures. We also perform qualitative testing by developing a hand controller and robot linked by an RAS. The interface is designed so that the RAS is interchangeable, allowing direct comparison of different RAS designs. A human operator uses the interface to complete a task, and the relative accuracy and subjective experience is compared for the RAS tested. The FCT is found to have lower static friction than all other tested RAS, higher stiffness than pneumatic cylinders, and comparable task performance to all tested RAS. Unique characteristics of the FCT, limitations of the testing system, and recommendations for future work are discussed.
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    Understanding the Impact of Artificial Intelligence on Higher Education
    (2023-06-08) Eaton, Sarah Elaine; Dawson, Phillip; McDermott, Brenda; Brennan, Robert; Wiens, Jason; Moya, Beatriz; Dahal, Bibek; Milne, Nick; Miller, Allyson; Mindzak, Michael; Kumar, Rahul; Hamilton, Melanie
    This one-day public conference included transdisciplinary research presentations on various topics related to artificial intelligence in higher education including, but not limited to, pedagogy, assessment, ethics, artificial intelligence, ChatGPT, large language models, bias, equity, diversity, inclusion Sponsors include: Social Sciences and Humanities Research Council (SSHRC) (Grant #: 611-2022-0398) Social Sciences and Humanities Research Council of Canada (SSHRC) University of Calgary International Research Partnership Workshop Grant University of Calgary Teaching and Learning Grant Werklund School of Education, University of Calgary Deakin University Brock University Toronto Metropolitan University University of Saskatchewan