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Browsing by Author "Pate, Jeremy"

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    Empowering Compartmental Modeling With Mobility and Shelter-in-Place Analysis
    (Frontiers, 2021-04-29) Ramezani, Somayeh Bakhtiari; Rahimi, Shahram; Amirlatifi, Amin; Hudnall, Matthew; Pate, Jeremy; Penmetsa, Praveena; Qian, Xinwu
    A model that is capable of handling the non-linear trend of COVID-19 throughout the US and evaluate different effects of interstate/intrastate mobility measures can help decision-makers adjust guidelines and state-wide mandates to contain the pandemic's spread. The abundance of cellular-based data has made it possible to study many aspects of users' mobility, including their travel, contact, and dwell patterns. This study uses a compartmental metapopulation model to present a correlation between the contact and mobility indices and the likelihood of being susceptible to infection. We studied the effect of travel from other states on overall infections in a destination state and observed a strong inverse correlation of 0.98 between the contact index and social awareness compartment, i.e., individuals who are no longer susceptible to infection. The shelter-in-place what-if analysis for travelers from other states on the course of infection in the destination state showed a possible reduction of over 22% in the total number of infections and death if travelers sheltered in place for 5–7 days.
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    Improving intelligent analytics through guidance: analysis and refinement of patterns of use and recommendation methods for data mining and analytics systems
    (University of Alabama Libraries, 2019) Pate, Jeremy; Dixon, Brandon; University of Alabama Tuscaloosa
    In conjunction with the proliferation of data collection applications, systems that provide functionality to analyze and mine this resource also increase in count and complexity. As a part of this growth, understanding how users navigate these systems, and how that navigation influences the resulting extracted information and subsequent decisions becomes a critical component of their design. A central theme of improving the understanding of user behavior and tools for their support within these systems focuses the effort to gain a context-aware view of analytics system optimization. Through distinct, but interwoven, articles this research examines the specific characteristics of usage patterns of a specific example of these types of systems, construction of and educational support system for new and existing users, and a decision-tree supported workflow optimization recommender system. These components combine to yield a method for guided intelligent analytics that uses behavior, system knowledge, and workflow optimization to improve the user experience and promote efficiency of use for systems of this type.