No Apparat Programme Today

December 16th, 2005 | music

No time. It’ll be back in 2006. In the meantime, you can download all nine previous Programmes with the links below (all tracklistings can be found by clicking the “podcasts” category in the left hand menu bar), or listen to them right on the page using the PlayTagger system (the little play button should appear next to each link if you have Javascript available).

Direct downloads of previous Programmes: 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9


Catastrophic Radiation Levels In Chechnya

December 16th, 2005 | researchmaterial

Prosecutors in Chechnya are looking into how “catastrophic” levels of radioactivity were recorded at a factory in the Russian republic.

Radioactive levels at the plant were half those recorded at the Chernobyl plant in 1986, Russian TV reports. Investigators said the radiation posed a danger to people living near it in the region’s capital, Grozny.

The case has raised fears militants could use radioactive waste to build a crude nuclear bomb.

Radioactive materials have a variety of uses in the manufacturing industry. If not disposed of properly, radioactive waste can pose a serious threat to people nearby.

Chechen prosecutor Valery Kuznetsov is quoted by the Associated Press news agency as saying the failure to remove the radioactive material or isolate access to the plant had made it “a threat to the population”. Radiation levels at one storage facility in the plant were 58,000 times higher than normal levels…


Artificial Neural Network Decides Movie Success Even Before Shooting: Cinema Dies

December 16th, 2005 | researchmaterial

Will the 3-hour special-effects-loaded remake of King Kong be a box office smash or a complete turkey? For movie producers, getting such questions right can be worth millions, and now they have a computer system to help them work it out before a film is even made.

The idea comes from Ramesh Sharda, an information scientist at Oklahoma State University in Stillwater, who has trained an artificial neural network to recognise what makes a successful movie.

Using data on 834 movies released between 1998 and 2002, Sharda found that the neural network can judge a film based on seven key parameters: the “star value” of the cast, the movie’s age rating, the time of release against that of competitive movies, the film’s genre, the degree of special effects used, whether it is a sequel or not, and the number of screens it is expected to open in. This allowed it to place a movie in one of nine categories, ranging from “flop” (total takings less than $1 million) to “blockbuster” (over $200 million).

The system cannot take into account the intricacies of the plot, but Sharda says it can nonetheless get the revenue category spot-on 37 per cent of the time, and correct to within one category either side 75 per cent of the time. This is enough to make the system a “powerful decision aid”, Sharda says…


December 16th, 2005 | people I know

name
Matt Fraction
on filmmaking


It’s almost as good as the day we had the giant screaming lady, the trained chihuahuas, the family of Mexican wrestlers and the three Tibetan monks on go-carts.