DukeJava

cross-posted from: https://aus.social/users/ajsadauskas/statuses/110383494811653617

Melbourne Airport Rail workers redeployed as project officially paused.

A really disappointing, backwards step here from the Victorian government.

And yes, stopping and then restarting a major infrastructure project (if that's what ends up happening) is almost certain to lead to delays and cost blowouts, when compared to just completing construction.

From The Age:

"Hundreds of tradespeople will be seconded to other projects after the Andrews government confirmed Melbourne Airport Rail Link construction would be paused, awaiting the results of a major Commonwealth review of the country’s infrastructure pipeline.

"Deputy Premier Jacinta Allan on Wednesday ended weeks of speculation about the future of the long-awaited rail line, saying works would be temporarily halted on the $13 billion Airport Rail Link, as well as upgrades of Clyde, McGregor and Racecourse roads."

https://www.theage.com.au/politics/victoria/melbourne-airport-rail-workers-redeployed-as-project-officially-paused-20230517-p5d93a.html

#trains #cities #Melbourne #Victoria #VicPol #Auspol @fuck_cars @australia #news #politics #train #urbanism #UrbanPlanning

The regular elo formula is complicated.

The most basic elo formula is win = 1 points, draw = 0, lose = -1. Which is a little too basic.

I looked around and couldn't find a 'medium difficulty' elo formula. Anyone have a medium difficulty proposal?

Regular elo formula:

The Elo rating system embodies this by using a formula that changes a player's rating by adding K(S-E) to his rating each time. K is a constant that is the same for all players; the higher it is, the more easily your rating changes. S is the score of the player in a match (+1 for a win, 0 for a loss). E is the expected score of the player in the match. Against a weak player, it is close to 1 since you expect a strong player to beat a weak player most of the time. Conversely, against a stronger player, it is close to 0. You can calculate E using the formula E_A = 1/(1+10(R_B-R_A/400)), where E_A is the expect score of player A with rating R_A when faced with player B with rating R_B.

cross-posted from: https://lemmy.ml/post/575485

R-selection is like having 1000 offsprings, whereas k-selection is like having only 1.

I heard a variation applied to humans in a psychology textbook about how abused humans are more likely to have more kids than unabused and cannot find the name of this theory