Words to dust

something like a phenomenon
moma:

Robert Heinecken: Object Matter closes 9/7 (and contains selfie-applicable posing tips). 
[Robert Heinecken. Lessons in Posing Subjects/Matching Facial Expressions. 1981. Collection UCLA Grunwald Center for Graphic Art, Hammer Museum, Los Angeles. Gift of Dean Valentine and Amy Adelson. © 2014 The Robert Heinecken Trust]

moma:

Robert Heinecken: Object Matter closes 9/7 (and contains selfie-applicable posing tips). 

[Robert Heinecken. Lessons in Posing Subjects/Matching Facial Expressions. 1981. Collection UCLA Grunwald Center for Graphic Art, Hammer Museum, Los Angeles. Gift of Dean Valentine and Amy Adelson. © 2014 The Robert Heinecken Trust]

thisiscitylab:


If “Goldilocks and the Three Bears” were written today, bike-share stations would play the role of the porridge. A station that’s too full is a bad thing, because that means riders can’t return a bike there. A station that’s too empty is also a bad thing, because that means potential riders can’t rent from there. To keep members happy, you need to get the number of bikes at a station just right.
Operators know this as the "rebalancing" problem, and it’s not nearly as easy to resolve as it might seem. On the contrary, some of the world’s top mathematicians and computer scientists are addressing the challenge right now. In this week’s issue of Science, Vienna correspondent Chelsea Wald reports that as many as 30 researchers are devoting serious time to rebalancing—some in collaboration with bike-share operators in major cities.
The goal of this research is to derive algorithms directing the vans and trucks that bike-share operators use to shuffle bikes from station to station within a city. Trouble is, rebalancing is a moving target with several layers of complexity. You not only need to predict how many bikes a station will need at a certain time, but you need to minimize the (costly and time-consuming) movement of these vans and trucks—and you need to do it all while the system is in use.

-Balancing Bike-Share Stations Has Become a Serious Scientific Endeavor
[Graphic: Rainer-Harbach et al (2014)]

thisiscitylab:

If “Goldilocks and the Three Bears” were written today, bike-share stations would play the role of the porridge. A station that’s too full is a bad thing, because that means riders can’t return a bike there. A station that’s too empty is also a bad thing, because that means potential riders can’t rent from there. To keep members happy, you need to get the number of bikes at a station just right.

Operators know this as the "rebalancing" problem, and it’s not nearly as easy to resolve as it might seem. On the contrary, some of the world’s top mathematicians and computer scientists are addressing the challenge right now. In this week’s issue of Science, Vienna correspondent Chelsea Wald reports that as many as 30 researchers are devoting serious time to rebalancing—some in collaboration with bike-share operators in major cities.

The goal of this research is to derive algorithms directing the vans and trucks that bike-share operators use to shuffle bikes from station to station within a city. Trouble is, rebalancing is a moving target with several layers of complexity. You not only need to predict how many bikes a station will need at a certain time, but you need to minimize the (costly and time-consuming) movement of these vans and trucks—and you need to do it all while the system is in use.

-Balancing Bike-Share Stations Has Become a Serious Scientific Endeavor

[Graphic: Rainer-Harbach et al (2014)]