Less is more: energy-efficient mobile sensing with SenseLess

Workshop held as part of ACM SIGCOMM 2009We present SenseLess, a system that leverages the different energy consumption characteristics of sensors to maximise battery life in mobile-sensing applications. We use the less expensive sensors more often, thereby enabling us to use the more expensive sensors less frequently. In the context of location-aware services, experimental results indicate that for a typical indoor and outdoor walk, compared to a simple GPS-based system, our SenseLess system can reduce energy consumption by more than 58% when determining a user's location, while maintaining the fidelity of the sensed data. This extends the battery life of a typical handheld device from 9 hours to 22 hours.Postprin

Assessing the use of social media in physician assistant education.

Objectives: This study aims to assess physician assistant (PA) students\u27 experiences with social media (SM) as a part of their medical education. Methods: The study is split into two phases: Phase 1- A cross-sectional survey emailed to all PA students at four PA school campuses to assess students\u27 prior SM experiences (226 responses, 71.1% response rate); and Phase 2- Inclusion of SM educational resources, via Twitter, within lectures performed at two PA schools. A phase-2 survey assessed students\u27 opinions of educational SM (50 responses, 59.5% response rate) and SM usage was tracked. Results: The phase-1 survey respondents indicated that 97.3% (n=220) use social media; often used as a part of their education, 65% (n=147) informally and 2.7% (n=6) formally incorporated. Students most commonly use Facebook, YouTube, and Instagram, but rarely use Twitter. Currently using SM for medical education was significantly associated with predicting that future PA education will formally include SM [r Conclusions: Many PA students are currently using various forms of social media to augment their education. Most PA students support formal incorporation of social media into their education. PA educators should consider using our data and methods of social media inclusion when designing curricula and while clinically precepting PA students

Stochastic Simulation of Process Calculi for Biology

Biological systems typically involve large numbers of components with complex, highly parallel interactions and intrinsic stochasticity. To model this complexity, numerous programming languages based on process calculi have been developed, many of which are expressive enough to generate unbounded numbers of molecular species and reactions. As a result of this expressiveness, such calculi cannot rely on standard reaction-based simulation methods, which require fixed numbers of species and reactions. Rather than implementing custom stochastic simulation algorithms for each process calculus, we propose to use a generic abstract machine that can be instantiated to a range of process calculi and a range of reaction-based simulation algorithms. The abstract machine functions as a just-in-time compiler, which dynamically updates the set of possible reactions and chooses the next reaction in an iterative cycle. In this short paper we give a brief summary of the generic abstract machine, and show how it can be instantiated with the stochastic simulation algorithm known as Gillespie's Direct Method. We also discuss the wider implications of such an abstract machine, and outline how it can be used to simulate multiple calculi simultaneously within a common framework.Comment: In Proceedings MeCBIC 2010, arXiv:1011.005