Analytic Methods for Optimizing Realtime Crowdsourcing

Realtime crowdsourcing research has demonstrated that it is possible to recruit paid crowds within seconds by managing a small, fast-reacting worker pool. Realtime crowds enable crowd-powered systems that respond at interactive speeds: for example, cameras, robots and instant opinion polls. So far, these techniques have mainly been proof-of-concept prototypes: research has not yet attempted to understand how they might work at large scale or optimize their cost/performance trade-offs. In this paper, we use queueing theory to analyze the retainer model for realtime crowdsourcing, in particular its expected wait time and cost to requesters. We provide an algorithm that allows requesters to minimize their cost subject to performance requirements. We then propose and analyze three techniques to improve performance: push notifications, shared retainer pools, and precruitment, which involves recalling retainer workers before a task actually arrives. An experimental validation finds that precruited workers begin a task 500 milliseconds after it is posted, delivering results below the one-second cognitive threshold for an end-user to stay in flow.Comment: Presented at Collective Intelligence conference, 201

Heparinase Immobilization Characterization and Optimization a

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73755/1/j.1749-6632.1988.tb25880.x.pd

EXPERIMENTAL IMPLEMENTATION OF INTEGRATOR BACKSTEPPING AND PASSIVE NONLINEAR CONTROLLERS ON THE RTAC TESTBED

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/57811/1/BenchmarkIJRNCBuppIJRNC1998.pd

A BENCHMARK PROBLEM FOR NONLINEAR CONTROL DESIGN

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/57785/1/BenchmarkIJRNCproblemIJRNC1998.pd

Finite Settling Time Control of the Double Integrator Using a Virtual Trap-Door Absorber

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/57813/1/TrapDoorTAC2000.pd

Crowds in two seconds: Enabling realtime crowd-powered interfaces

Interactive systems must respond to user input within seconds. Therefore, to create realtime crowd-powered interfaces, we need to dramatically lower crowd latency. In this paper, we introduce the use of synchronous crowds for on-demand, realtime crowdsourcing. With synchronous crowds, systems can dynamically adapt tasks by leveraging the fact that workers are present at the same time. We develop techniques that recruit synchronous crowds in two seconds and use them to execute complex search tasks in ten seconds. The first technique, the retainer model, pays workers a small wage to wait and respond quickly when asked. We offer empirically derived guidelines for a retainer system that is low-cost and produces on-demand crowds in two seconds. Our second technique, rapid refinement, observes early signs of agreement in synchronous crowds and dynamically narrows the search space to focus on promising directions. This approach produces results that, on average, are of more reliable quality and arrive faster than the fastest crowd member working alone. To explore benefits and limitations of these techniques for interaction, we present three applications: Adrenaline, a crowd-powered camera where workers quickly filter a short video down to the best single moment for a photo; and Puppeteer and A|B, which examine creative generation tasks, communication with workers, and low-latency voting

Ariel - Volume 6 Number 2

Editors Mark Dembert J.D. Kanofsky Frank Chervenak John Lammie Curt Cummings Entertainment Robert Breckenridge Joe Conti Gary Kaskey Photographer Larry Glazerman Overseas Editor Mike Sinason Humorist Jim McCann Staff Ken Jaffe Bob Skarloff Halley Faust Jim Burk

Investigation of Cumulative Retrospective Cost Adaptive Control for Missile Application

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/83634/1/AIAA-2010-7577-578.pd