HN user
The article says 1/3 are "at risk" of depression. It looks like the statistic is based on a web survey (https://pdfs.semanticscholar.org/9ac3/478bc1263be53f5150a54b...), so I suppose they couldn't do an actual diagnosis.
Why are GA aircraft so expensive? A C172 seems much simpler mechanically than a car. I can see that the price would be driven up by low volume and probably a much stricter QA/inspection process... Is that it, or am I missing something?
The NABirds dataset: http://dl.allaboutbirds.org/nabirds.
But it's North American birds, not sure if you specifically want to cover birds that show up in Finland or if that was just your inspiration.
There are a couple apps that do what you're talking about, but they're both North American birds only as well.
http://www.birdsnap.com/ (I was involved in this one)
We wrote Google to ask the reason for this sudden move and they responded that AdNauseam had breached the Web Store’s terms of service, stating that “An extension should have a single purpose that is clear to users…”
They deserve shit for lying.
Is there some evidence that changing the terminology this way has an effect -- say an increase in prosecutions or safer driving habits? I was surprised to come to the end of the article without anything about this one way or the other.
That's what a "false positive" is but Wikipedia also has a separate article on "false positive rate", which gives the formula
FP / (FP + TN)
Where FP is number of false positives, and TN is number of true negatives. So it's a third option:
- Out of 1000 actually negative samples, 50 were tested as positive.
So in the case of 1000 samples, 949 correctly testing as negative, 50 incorrectly testing as positive, and 1 correctly testing as positive, the false positive rate is 50 / 999.
FYI in this case the error was in Ukrainian-to-Russian translation, not Russian-to-English.
It's describing the dynamics in the (non-inertial) reference frame of the satellite (the reference frame in which the astronauts can be described as "floating around"). In this reference frame, the centrifugal force balances the gravitational force, leading to zero net acceleration.
"i" is different. Don't see anything else though.
I don't know much about how most unions work, but at least TV & movie actors and writers, classical musicians, and professional athletes have unions that work as task_queue describes. It's hard for me to imagine a programmer's union that didn't work this way getting off the ground.
I think the point of code signing is to ensure that the program was really written by Dropbox, so _if_ you trust Dropbox you should trust the program. That trust should definitely include both Dropbox's good intentions and their competency to prevent their payload system from being subverted.
I'm surprised you can sign an executable, then modify it while preserving the validity of the signature, as I always though this is exactly what code signing is meant to prevent. Can anyone who knows more about this than me (a low bar!) explain whether this is a flaw in the signing mechanism or is actually okay?
The Priceonomics article's main point is that raising speed limits doesn't (much) raise actual speed, so it's not inconsistent with papers (like the one you linked) that show that increased speed causes more and worse accidents.
This is consistent with most drivers behaving like _archon_ (and like me). For example, if every driver thinks she can safely drive 90 mph, but 80%, like _archon_ and me, stay below 10 over the limit out of fear of police, while 20% drive as fast as they like, then raising the limit from 60 to 70 will have no effect on the 85th percentile.
The article seems to quietly conflate the fastest 15% of drivers ignoring the limit with "most drivers" ignoring the limit. Which is odd. However, even under the _archon_ model, increasing the limit would lead to a reduction in speed variance.
What is he misunderstanding? There's nothing in the post mentioning copyright or suggesting the author thinks he has a legal case. He just thinks New Relic are being jerks.
Maybe add iPod Touch to the not supported list in the app description. Although I know there aren't many of us!
Defense job creation is appealing because it's an easy way to use federal money for local benefit. If you want to fix bridges or something, you have to deal with people saying it's your state's or city's responsibility, but everyone agrees that defense is the feds' job.
I've been assuming the use case is that you're not in a store. The world is Amazon's showroom.
The article blithely describes the "best" strategy, without defining "best." I believe the strategy is only best in the sense of giving the highest probability of ending up with the best candidate--so the second best candidate is considered as bad as the worst.
The linked article (title "Painless Resumes With Markdown") doesn't even mention GitHub.
From the article:
... we lie, on average, three times during a routine ten-minute conversation with a stranger or casual acquaintance. Hardly anyone refrains from lying altogether, and some people report lying up to twelve times within that time span.
It sounds like there's a large variance; maybe the author is on the "twelve times" side of the distribution. Or maybe I'm naive. I can't imagine telling someone I like a restaurant just because he does, or giving a false compliment without a concrete reason.
(I'm American.)
This idea applies to more than medicine. A boss once told me, speaking about a piece of work I thought was pretty good, "If it could be better, it's wrong." It stuck with me, and I've found that everyone I meet who is exceptional at some skill has this attitude.
Children are not legally compelled to join Facebook and Google+.
The method at least is very different. The Google app is doing structure from motion, which essentially uses parallax to get the 3D shape of the scene. From there, you can blur/deblur according to depth. The Nokia app uses focal sweep, i.e. it just takes lots of pictures of the same scene focussed at different depths. I'm not sure what the pros and cons of each approach are.
You are right that they assume the subject is looking at a face, and so will always produce "face-like" output.
The paper includes a quantitative evaluation, in which they take a set of 30 distractor face images not used elsewhere in the study, and for each of them determine whether the reconstructed face is more similar to it, or to the original face the subject was looking at. On average, the reconstructed face is closer to the correct face than the distractor 62.5% of the time.
So it's better than random, and I think it's pretty cool work, but the quality of the reconstructions is pretty terrible, considering that a randomly chosen distractor will usually be very different from the test face (~half the time opposite sex, frequently different race, different age, etc). For comparison, it would be interesting to evaluate some simple, obviously terrible reconstructions by the same metric. For example, we could "reconstruct" the face as a image that is a single, solid color, the average RGB value of the pixels in the original face. Another "reconstruction" that it seems would very likely do better under this evaluation metric is something like the "race-gender-age" of perp descriptions in the news ("white male in his thirties").
A solo founder can have a team (of non-founders), as the founder in this article does.
The "perfectly valid" assumption is also definitely invalid, even within the U.S. A few counterexamples in NYC: "Broadway," "The Bowery," "Avenue of the Americas." Boston has "The Fenway." Many rural addresses are in the style of "300 State Route 20."
You're one for three.
Different societies have determined different things. Indian society in particular has determined that reducing this reward to risk-takers in order to widen access to drugs is a worthwhile trade.