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Spring 2020
Reinforcement learning (RL) is a powerful learning paradigm in which agents can learn to maximize sparse and delayed reward signals. Although RL has had many impressive successes in complex domains, learning can take hours, days, or even years of training data. A major challenge of contemporary...
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Spring 2022
Sajjadi Ghaemmaghami, Saeedehsadat
Today’s users are spending more time on web applications. Many users browse web applications and navigate through different web pages. They may have different interests, especially when it comes to large-scale applications. The more the developers of the applications know about their users’ needs...
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Spring 2010
Interest in park services and understanding leisure decision making has become increasingly important in the last fifty years. Canadians in particular have an affinity for spending time in natural areas and often in parks. Parks and protected areas provide a reasonable and approachable place for...
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User Experience with Brain-Computer Interface (BCI) Devices for Leisure: A Qualitative Study
DownloadSpring 2024
In this study, I explore the experiences of individuals with disabilities with brain-computer interface (BCI) technology to access leisure activities. The goal of the study was to understand the user experience, to inform BCI development and implementation by meeting the unique needs of users who...
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Fall 2023
Recommendation systems have become an indispensable part of our lives, providing an effective solution to information overload and enhancing user satisfaction by suggesting the most relevant content. In recent years, deep learning has facilitated the creation of recommendation technologies that...
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Spring 2019
The vital role of interior design is gradually being realized due to its frequent interaction with the occupant and significant influence on building performance regarding living experience and indoor environmental effects. However, the current practice of interior design is inefficient and...
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Spring 2017
Paper-making processes are large-scale two-dimensional systems. For these systems, the performance along both the machine direction (MD) and cross direction (CD) needs to be ensured for successful paper production. This thesis studies the robust tuning problem of MD and CD Model Predictive...