Browsing by Author "Guinness, Darren, 1990-"
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Item Models for rested touchless gestural interaction.(2015-07-31) Guinness, Darren, 1990-; Poor, G. Michael.Touchless mid-air gestural interaction has gained mainstream attention with the emergence of off-the-shelf commodity devices such as the Leap Motion and the Xbox Kinect. One of the issues with this form of interaction is fatigue, a problem colloquially known as the "Gorilla Arm Syndrome.'' However, by allowing interaction from a rested position, whereby the elbow is rested on a surface, this problem can be limited in its effect. In this paper we evaluate 3 possible methods for performing touchless mid-air gestural interaction from a rested position: a basic rested interaction, a simple calibrated interaction which models palm positions onto a hyperplane, and a more complex calibration which models the arm's interaction space using the angles of the forearm as input. The results of this work found that the two modeled interactions conform to Fitts's law and also demonstrated that implementing a simple model can improve interaction by improving performance and accuracy.Item Recommendations Made Easy(2014-06-23) Guinness, Darren, 1990-; Karbasi, Seyedeh Paniz, 1986-; Nazarov, Rovshen; Speegle, Gregory David.Fueled by ever-growing data, the need to provide recommendations for consumers, and the considerable domain knowledge required to implement distributed large scale graph solutions we sought to provide recommendations for users with minimal required knowledge. For this reason in this paper we implement a generalizable 'API-like' access to collaborative filtering. Three algorithms are introduced with three execution plans in order to accomplish the collaborative filtering functionality. Execution is based on memory constraints for scalability and our initial tests show promising results. We believe this method of large-scale generalized 'API-like' graph computation provides not only good trade-off between performance and required knowledge, but also the future of distributed graph computation.