This paper (whose extended journal version has been recently accepted) proposes a hierarchical Markov model that learns and infers a user’s daily movements.
Archive for January, 2007
Learning and Inferring Transportation Routines
Wednesday, January 31st, 2007Portable Reputations
Friday, January 19th, 2007In UTIFORO (a new research project), we may explore how sellers may “port” their reputation from eBay to informal markets. That might relate to this:
Last year I mentioned eBay’s Feedback system and said it was arguably their biggest asset. Even with its flaws, I said, it is one the biggest drivers of trust between two people buying and selling who’ve never met and never will. But it’s a closed system, usable only within eBay and only for eBay transactions.
We needed an internet-wide identity and feedback system that any reputable application can tap into, both pulling and pushing data.
At the time we had taken a look at iKarma, but they seemed to have missed the boat by ignoring the portability aspect of reputation.
Rapleaf launched in April. And while it’s still quite early, it does exactly what we need it to do – provide a good off-ebay reputation system. eBay banned Rapleaf in May (They learned their lesson with PayPal it seems), but the company is still chugging along.
Nissan tests intelligent transportation system
Friday, January 19th, 2007by Jonathan Goddard
20 September 2006 – Nissan is testing a newly developed intelligent transportation system, which it is hoped will allow vehicle-to-infrastructure communication to reduce traffic accidents and ease congestion.
The test, slated to begin on 1 October and conclude in 2009, is in Kanagaw – 25km from Tokyo. Around 10,000 drivers, who must be subscribers to Nissan’s CARWINGS navigation service, are expected to participate.
The advanced road traffic system uses information obtained from nearby vehicles and roadside optical beacons to alert drivers to potential danger from approaching vehicles. The information is received by an onboard antenna on the vehicle, and the system uses the information to warn drivers when they are speeding in restricted zones. It also provides drivers with fastest-route information using “probe data” – information on the position and speed of vehicles obtained by wireless communications technology.
Based on the results of the test, Nissan is planning to implement its intelligent transportation system in Japan and then globally in the future as part of its efforts to help reduce traffic accidents and congestion. In Japan, Nissan has set a target of halving the number of traffic fatalities or serious injuries involving Nissan vehicles by 2015 compared with the 1995 level
Bluetooth and GPS on chip
Tuesday, January 16th, 2007Animal Tags for People?
Friday, January 12th, 2007Two cousin companies bet the fast-expanding market for animal RFID chips will extend to humans before long
… Digital tags are expected to be affixed to the U.S.’s 40 million farm animals to enable regulators to track and respond quickly to disease, bioterrorism, and other calamities. Opponents have many fears about this plan, among them that it could be the forerunner of a similar system for humans. …
Well, all you conspiracy buffs, let me introduce you to Kevin McGrath and Scott Silverman. … more
BitTyrant: a selfish BitTorrent client that improves performance
Friday, January 5th, 2007BitTyrant is a BitTorrent client with a novel unchoking algorithm.
Suppose your upload capacity is 50 KBps. If you’ve unchoked 5 peers, existing clients will send each peer 10 KBps, independent of the rate each is sending to you. In contrast, BitTyrant will rank all peers by their receive / sent ratios, preferentially unchoking those peers with high ratios.
During evaluation testing on more than 100 real BitTorrent swarms, BitTyrant provided an average 70% download performance increase when compared to the existing Azureus 2.5 implementation, with some downloads finishing more than three times as quickly.
I wonder how well it performs in swarms of other BitTyrant clients?
The USENIX paper is here.
Update: it seems to be using the same faster than the bear algorithm I came up with last year. Damn it, I should have tried it out. 