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dc.contributor.authorVilwock, William
dc.date.accessioned2020-04-30T10:07:42Z
dc.date.available2020-04-30T10:07:42Z
dc.date.issued2014-04-01
dc.identifier.urihttps://scholars.carroll.edu/handle/20.500.12647/3395
dc.description.abstractAs the number of worldwide cellular subscriptions approaches the world’s population, the negative effects of cell phone disruption have become increasingly apparent. In recent years, mobile phones have become advanced enough to moderate interruptions based on whether or not the user would want an interruption. Research into the area of interruption management has provided models and architecture for the creation of such an application. However, to our knowledge, there are no interruption management systems currently available in the Android or iPhone app stores using a probabilistic model to moderate cell phone interruptions. A probabilistic model would be an improvement over current binary decision models, which either lack accuracy, or require the user to predetermine every possible outcome. In this project, we have employed a probabilistic model to implement an interruption management system for Android OS 4.0 that uses five contexts: schedule, time of day, location, caller relationship and driving. Our system intercepts the call, calculates the probability an interruption is desirable, and then changes the phone’s audio profile to vibrate, silent, or ring based on our model. A missed notification service has also been implemented to alert the user, at an appropriate time, that he has missed notifications.
dc.subjectsmart phone, cell phone, disruption, interruption
dc.titleImplementation Of A Probabilistic Interruption Management System For Smartphones
dc.typethesis
carrollscholars.object.degreeBachelor's
carrollscholars.object.departmentMathematics, Engineering & Computer Science
carrollscholars.object.disciplinesApplied Mathematics; Computer Sciences; Software Engineering
carrollscholars.legacy.itemurlhttps://scholars.carroll.edu/mathengcompsci_theses/18
carrollscholars.legacy.contextkey10978528
carrollscholars.object.seasonSpring
dc.date.embargo12/31/1899 0:00


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