Processing Neurology Clinical Data for Knowledge Discovery: Scalable Data Flows Using Distributed Computing

Author(s):  
Satya S. Sahoo ◽  
Annan Wei ◽  
Curtis Tatsuoka ◽  
Kaushik Ghosh ◽  
Samden D. Lhatoo
2018 ◽  
Vol 16 (1) ◽  
pp. 20-38 ◽  
Author(s):  
Mark Andrew Wood ◽  
Chrissy Thompson

Speed camera ‘traps’, random breath testing (RBT) stations, and other forms of mobile traffic surveillance have long been circumvented by motorists. However, as technologies for traffic surveillance have developed, so too have technologies enabling individuals to monitor and countersurveil these measures. One of the most recent forms of these countersurveillance platforms can be found on Facebook, where dedicated regional and national RBT and ‘police presence’ pages publicly post the locations of various forms of police surveillance in real-time. In this article, we argue that Facebook RBT pages exemplify a new form of social media facilitated countersurveillance we term crowdsourced countersurveillance: the use of knowledge-discovery and management crowdsourcing to facilitate surveillance discovery, avoidance, and countersurveillance. Crowdsourced countersurveillance, we argue, represents a form of countersurveillant assemblage: an ensemble of individuals, technologies, and data flows that, more than the sum of their parts, function together to neutralize surveillance measures. Facilitated by affordances for crowdsourcing, aggregating, and crowdmapping geographical data information on surveillance actors, crowdsourced countersurveillance provides a means of generating ‘hybrid heterotopias’: mediated counter-sites that enable individuals to contest and circumvent surveilled spatial arrangements.


2018 ◽  
Author(s):  
Martin G. Seneviratne ◽  
Michael G. Kahn ◽  
Tina Hernandez-Boussard

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