5,479 research outputs found
UMSL Bulletin 2023-2024
The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp
The experience of using role-play and simulated practice as an adjunct to paramedic placement learning
This study examines the current experiences of paramedic students regarding the perceptions, understanding and utilisation of role-play plus simulation in a paramedic degree programme. This area is underexplored, so it is situated in the context of paramedic practice, training and education landscape in UK, Australia, Canada and the USA, and cognate professions.The skills training in its original format remains, as does the on-the job clinical training (hospital placement and ambulance internship) as these are set regulatory requirements. Role-play and task focused simulation is used as part of syndicate learning for skills development. A mixed methodology, comprising both qualitative and quantitative approaches, including an exploratory sequential design, was used in this research. This was done in order to evaluate the student perceptions of their current placement experience and to explore the perception of combining simulation and role-playing.The study results show that the current educational model of clinical placement is flawed. After a brief exposure to an exemplar event, students preferred the combination of simulation and role-playing over the use of either technique independently. Adoption of this technique firstly requires a set definition of terminology and consistent interpretation within the discipline.A consolidation of the students’ experience is required by enhancing the mentorship supports. Further research is needed to design and develop the combination of role-playing and simulation to enhance student learning in the simulation laboratory. This study promotes positive social change by providing data to the educators and key decision makers of the paramedic programme on students’ perceptions of the benefits of a technique that is able to support instruction and augment the students’ clinical placement experience
Beam scanning by liquid-crystal biasing in a modified SIW structure
A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium
Reinforcement learning in large state action spaces
Reinforcement learning (RL) is a promising framework for training intelligent agents which learn to optimize long term utility by directly interacting with the environment. Creating RL methods which scale to large state-action spaces is a critical problem towards ensuring real world deployment of RL systems. However, several challenges limit the applicability of RL to large scale settings. These include difficulties with exploration, low sample efficiency, computational intractability, task constraints like decentralization and lack of guarantees about important properties like performance, generalization and robustness in potentially unseen scenarios.
This thesis is motivated towards bridging the aforementioned gap. We propose several principled algorithms and frameworks for studying and addressing the above challenges RL. The proposed methods cover a wide range of RL settings (single and multi-agent systems (MAS) with all the variations in the latter, prediction and control, model-based and model-free methods, value-based and policy-based methods). In this work we propose the first results on several different problems: e.g. tensorization of the Bellman equation which allows exponential sample efficiency gains (Chapter 4), provable suboptimality arising from structural constraints in MAS(Chapter 3), combinatorial generalization results in cooperative MAS(Chapter 5), generalization results on observation shifts(Chapter 7), learning deterministic policies in a probabilistic RL framework(Chapter 6). Our algorithms exhibit provably enhanced performance and sample efficiency along with better scalability. Additionally, we also shed light on generalization aspects of the agents under different frameworks. These properties have been been driven by the use of several advanced tools (e.g. statistical machine learning, state abstraction, variational inference, tensor theory).
In summary, the contributions in this thesis significantly advance progress towards making RL agents ready for large scale, real world applications
Machine learning and mixed reality for smart aviation: applications and challenges
The aviation industry is a dynamic and ever-evolving sector. As technology advances and becomes more sophisticated, the aviation industry must keep up with the changing trends. While some airlines have made investments in machine learning and mixed reality technologies, the vast majority of regional airlines continue to rely on inefficient strategies and lack digital applications. This paper investigates the state-of-the-art applications that integrate machine learning and mixed reality into the aviation industry. Smart aerospace engineering design, manufacturing, testing, and services are being explored to increase operator productivity. Autonomous systems, self-service systems, and data visualization systems are being researched to enhance passenger experience. This paper investigate safety, environmental, technological, cost, security, capacity, and regulatory challenges of smart aviation, as well as potential solutions to ensure future quality, reliability, and efficiency
Integrating materials supply in strategic mine planning of underground coal mines
In July 2005 the Australian Coal Industry’s Research Program (ACARP) commissioned Gary Gibson to identify constraints that would prevent development production rates from achieving full capacity. A “TOP 5” constraint was “The logistics of supply transport distribution and handling of roof support consumables is an issue at older extensive mines immediately while the achievement of higher development rates will compound this issue at most mines.” Then in 2020, Walker, Harvey, Baafi, Kiridena, and Porter were commissioned by ACARP to investigate Australian best practice and progress made since Gibson’s 2005 report. This report was titled: - “Benchmarking study in underground coal mining logistics.” It found that even though logistics continue to be recognised as a critical constraint across many operations particularly at a tactical / day to day level, no strategic thought had been given to logistics in underground coal mines, rather it was always assumed that logistics could keep up with any future planned design and productivity. This subsequently meant that without estimating the impact of any logistical constraint in a life of mine plan, the risk of overvaluing a mining operation is high.
This thesis attempts to rectify this shortfall and has developed a system to strategically identify logistics bottlenecks and the impacts that mine planning parameters might have on these at any point in time throughout a life of mine plan. By identifying any logistics constraints as early as possible, the best opportunity to rectify the problem at the least expense is realised. At the very worst if a logistics constraint was unsolvable then it could be understood, planned for, and reflected in the mine’s ongoing financial valuations. The system developed in this thesis, using a suite of unique algorithms, is designed to “bolt onto” existing mine plans in the XPAC mine scheduling software package, and identify at a strategic level the number of material delivery loads required to maintain planned productivity for a mining operation. Once an event was identified the system then drills down using FlexSim discrete event simulation to a tactical level to confirm the predicted impact and understand if a solution can be transferred back as a long-term solution. Most importantly the system developed in this thesis was designed to communicate to multiple non-technical stakeholders through simple graphical outputs if there is a risk to planned production levels due to a logistics constraint
A motion control method for a differential drive robot based on human walking for immersive telepresence
Abstract. This thesis introduces an interface for controlling Differential Drive Robots (DDRs) for telepresence applications. Our goal is to enhance immersive experience while reducing user discomfort, when using Head Mounted Displays (HMDs) and body trackers. The robot is equipped with a 360° camera that captures the Robot Environment (RE). Users wear an HMD and use body trackers to navigate within a Local Environment (LE). Through a live video stream from the robot-mounted camera, users perceive the RE within a virtual sphere known as the Virtual Environment (VE). A proportional controller was employed to facilitate the control of the robot, enabling to replicate the movements of the user. The proposed method uses chest tracker to control the telepresence robot and focuses on minimizing vection and rotations induced by the robot’s motion by modifying the VE, such as rotating and translating it. Experimental results demonstrate the accuracy of the robot in reaching target positions when controlled through the body-tracker interface. Additionally, it also reveals an optimal VE size that effectively reduces VR sickness and enhances the sense of presence
Ready Pupil One: Online Learning Experiences of Undergraduate STEM Majors at a Midwest Regional Comprehensive University
Many institutions of higher education in the United States, and, indeed, around the world, are feeling multi-faceted pressures to offer course content through online delivery modes. Administrators of institutions of higher education often view such delivery as a way to raise revenue and reduce costs for the institution while also often offering students flexibility to learn at their own pace. Still, many students and faculty alike often also encounter challenges with online delivery. In this phenomenological qualitative study, I explored the positive and negative experiences of undergraduate STEM majors who had taken at least one major-required, STEM-focused, class delivered entirely online. Using a semi-structured interview format, I interviewed twenty-three undergraduate STEM majors at a mid-sized, public, four-year Regional Comprehensive University. Students described their learning experiences, which I then analyzed for emergent themes. The majority of participants reported feelings of isolation and loneliness in their classes, owing, primarily, to a lack of opportunity to interact with their peers in substantial ways. This study’s findings align with previous research suggesting that best practices for online synchronous and asynchronous instruction include giving students opportunities to learn collaboratively with peers and interact regularly with their professors
Anime Studies: media-specific approaches to neon genesis evangelion
Anime Studies: Media-Specific Approaches to Neon Genesis Evangelion aims at advancing the study of anime, understood as largely TV-based genre fiction rendered in cel, or cel-look, animation with a strong affinity to participatory cultures and media convergence. Making Neon Genesis Evangelion (Shin Seiki Evangerion, 1995-96) its central case and nodal point, this volumen forground anime as a media with clearly recognizable aesthetic properties, (sub)cultural affordances and situated discourses
International Academic Symposium of Social Science 2022
This conference proceedings gathers work and research presented at the International Academic Symposium of Social Science 2022 (IASSC2022) held on July 3, 2022, in Kota Bharu, Kelantan, Malaysia. The conference was jointly organized by the Faculty of Information Management of Universiti Teknologi MARA Kelantan Branch, Malaysia; University of Malaya, Malaysia; Universitas Pembangunan Nasional Veteran Jakarta, Indonesia; Universitas Ngudi Waluyo, Indonesia; Camarines Sur Polytechnic Colleges, Philippines; and UCSI University, Malaysia. Featuring experienced keynote speakers from Malaysia, Australia, and England, this proceeding provides an opportunity for researchers, postgraduate students, and industry practitioners to gain knowledge and understanding of advanced topics concerning digital transformations in the perspective of the social sciences and information systems, focusing on issues, challenges, impacts, and theoretical foundations. This conference proceedings will assist in shaping the future of the academy and industry by compiling state-of-the-art works and future trends in the digital transformation of the social sciences and the field of information systems. It is also considered an interactive platform that enables academicians, practitioners and students from various institutions and industries to collaborate
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