September 14th, 2005
Local governments and agencies are waking up with a start — could it happen here? If first responders cannot communicate with each other in the first 72 hours — how do they do their job?
The New Orleans tragedy manifested the worst communication nightmares imaginable — underground communication lines were disabled due to flooding, cell towers were blown over, backup generators ran out of fuel — or filled up with water. Radios of police, firefighters, ER couldn’t talk to each other. In some cases first responders were simply walking over to each other to talk!
Ad hoc networks boast of working in especially such situations … after more than 10 years and millions of $$ in research … where is the first deployed/working ad hoc network?
No sooner had a 46-truck convoy of Baltimore first-responders and equipment left for Louisiana on Sunday than it received an education in emergency communications: Even state-of-the-art systems can fail.
Grand Rapids Press:
“The lessons we can learn from the Katrina disaster is what happens to those with mobility and transportation issues. If there is a need for a mass evacuation, how would we get those without transportation?” 1st Ward Commissioner James Jendrasiak asked.
The Nevada Homeland Security Department is taking up the issue of disaster response. From their own experience and what they’ve seen with Hurricane Katrina relief, they’ve determined the channels of communication are broken.
July 13th, 2005
Recently both Yahoo! and Google released their Map APIs. Both have interesting and unique features – while Google map is easy to customize and embed in your website or application, all you need to do with Yahoo Map API is provide it with the XML formatted data for
plotting information on the map. The nice thing about Yahoo API vs Google API is that you do not need to specify the exact latitude and longitude information and it does the geocoding for you using the address.
Having played with both a little, I hacked up an application that would extract the latest news from Yahoo! US News website and display on the map. You can view it in action here and it has also been added on the yahoo developer network’s featured application list here. 😉
These APIs provide a simple way for anyone to visualize geospatial information and I hope that such nifty applications would motivate people to provide metadata information such as OPML or geocoding in images.
June 30th, 2005
Google Earth is a Java-based GIS application that allows users to find places on the face of the Earth. The users can zoom from space down to street level and combine imagery, 3D geography, maps, and business data to get the total picture in seconds.
I love it! If your computer meets these requirements, give it a try.
It took me 15 mins to find the place where I used live in Hong Kong in Google Earth.
June 21st, 2005
This is a fictionary 8-mintue mini-movie speculating the evolution of media from 1984 up until 2014 .
- ‘2005 â€“ In response to Googleâ€™s recent moves, Microsoft buys Friendster. ‘
- ‘2008 sees the alliance that will challenge Microsoftâ€™s ambitions. Google and Amazon join forces to form Googlezon.’
- ‘In 2011, the slumbering Fourth Estate awakes to make its first and final stand. The New York Times Company sues Googlezon…’
- ‘In year 2014, New York Times has gone offline.’
source: http://www.robinsloan.com/epic/; transcript
June 6th, 2005
IBM seems to have captured the gaming console market, becoming the sole chip provider for PS3, XBox 360 and Nintendo.
Apple moves on in search of greener pastures, switching to Intel x86 chips. Mac users will probably see dropped prices and increasing support for x86 applications by end of 2007. Seems to be win-win situation for Intel, Apple and Mac enthusiasts! We might finally see non-linux robust software on x86 after all ;).
April 18th, 2005
So the major players have joined in the WiMax game. This report from the Washington Post describes Intel coming to DC area to release their new WiMax chipset.
February 18th, 2005
There is an interesting paper that describes how TiVo computes its recording recommendations.
We describe the TiVo television show collaborative recommendation system which has been fielded in over one million TiVo clients for four years. Over this install base, TiVo currently has approximately 100 million ratings by users over approximately 30,000 distinct TV shows and movies. TiVo uses an item-item (show to show) form of collaborative filtering which obviates the need to keep any persistent memory of each userï¿½s viewing preferences at the TiVo server. Taking advantage of TiVoï¿½s client-server architecture has produced a novel collaborative filtering system in which the server does a minimum of work and most work is delegated to the numerous clients. Nevertheless, the server-side processing is also highly scalable and parallelizable. Although we have not performed formal empirical evaluations of its accuracy, internal studies have shown its recommendations to be useful even for multiple user households. TiVoï¿½s architecture also allows for throttling of the server so if more server-side resources become available, more correlations can be computed on the server allowing TiVo to make recommendations for niche audiences.