Nearly 50% of users used names, slang words, dictionary words or trivial passwords (consecutive digits, adjacent keyboard keys, and so on). The most common password is “123456”.

I have a major pet peeve that I need to confess. I go insane when I hear programmers talking about statistics like they know shit when it’s clearly obvious they do not. I’ve been studying it for years and years and still don’t think I know anything. This article is my call for all programmers to finally learn enough about statistics to at least know they don’t know shit. I have no idea why, but their confidence in their lacking knowledge is only surpassed by their lack of confidence in their personal appearance.

Even if terrorists were able to pull off one attack per year on the scale of the 9/11 atrocity, that would mean your one-year risk would be one in 100,000 and your lifetime risk would be about one in 1300. (300,000,000 ÷ 3,000 = 100,000 ÷ 78 years = 1282) In other words, your risk of dying in a plausible terrorist attack is much lower than your risk of dying in a car accident, by walking across the street, by drowning, in a fire, by falling, or by being murdered.

So do these numbers comfort you? If not, that's a problem. Already, security measures—pervasive ID checkpoints, metal detectors, and phalanxes of security guards—increasingly clot the pathways of our public lives. It's easy to overreact when an atrocity takes place—to heed those who promise safety if only we will give the authorities the "tools" they want by surrendering to them some of our liberty.

Piwik is a downloadable, open source (GPL licensed) web analytics software program. It provides you with detailed real time reports on your website visitors: the search engines and keywords they used, the language they speak, your popular pages… and so much more.

Piwik aims to be an open source alternative to Google Analytics.

To put it in more approachable terms, observe that Ecma-376, OOXML, at 6,045 pages in length, was 58 standard deviations above the mean for Ecma Fast Tracks. Consider also that the average adult American male is 5′ 9″ (175 cm) tall, with a standard deviation of 3″ (8 cm). For a man to be as tall, relative to the average height, as OOXML is to the average Fast Track, he would need to be 20′ 3″ (6.2 m) tall !

Our purpose is rather simple. We want to make the internet as open as possible. Currently only a select few corporations have a complete and useful index of the web. Our goal is to change that fact by crawling the web and releasing as much information about its structure and content as possible. We plan on doing this in a manner that will cover our costs (selling our index) and releasing it for free for the benefit of all webmasters. Obviously, this goal has many potential legal, financial, ethical and technical problems. So while we can't promise specific results, we can promise to work hard, share our results, and help make the internet a better and more open space.

Our figure shows the performance of a server when subject to parallel load. This kind of load is often generated in a so-called "Distributed denial of service attack".

Apache dies at about 4,000 parallel sessions. Yaws is still functioning at over 80,000 parallel connections.

In our benchmarks we were only able to push 35 MB/s on small instances. So the actual requests per seconds were dependent on the object size we were pushing. The limit was always ~35 MB/s. Our typical HTML pages were around 50 to 70 KB, so we couldn’t reach the desired requests per second as our instance was at its bandwidth limit.

Usually when one instance hits its resource limits you load balance multiple ones. HAProxy is a fine example for a very robust TCP/HTTP load balancer. The problem is though, that it will not increase your bandwidth as all your traffic has to go through this one HAProxy instance. So even when you load balance multiple instances, each one is capable of pushing ~35 MB/s (—> ~350 MB/s with 10 small instances), the bottleneck will still be at ~35 MB/s (aka the load balancer).

Jackson’s findings showed that outside of flu season, the baseline risk of death among people who did not get vaccinated was approximately 60 percent higher than among those who did, lending support to the hypothesis that on average, healthy people chose to get the vaccine, while the “frail elderly” didn’t or couldn’t. In fact, the healthy-user effect explained the entire benefit that other researchers were attributing to flu vaccine, suggesting that the vaccine itself might not reduce mortality at all.

The Current State of Web Privacy, Data Collection, and Information Sharing

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