Note that no constraints were made about the upper length of the password... only on its contents...and the restriction that I described on contents does not, in general, considerably simplify a brute-force checker (in fact, it would probably tend to complicate it). An 8 character password might be crackable in only a few seconds with today's fastest multicore GPU's, assuming that you knew in advance that it was not more than 8 characters... but without knowing the upper bounds of the domain to search, the problem gets massively more complex.
How about "Create a mixed-case password at least 8 characters long, having at least one upper case letter that is not in the initial position, at least one lower case letter, and at least one digit and one special symbol that are not in either of the final two positions, and which contains no english word that is more than 4 characters"?
...that the decision to use such a password (or perhaps more correctly, the lack of a decision to utilize a good password) would usually just be a response to either a necessity or else a merely common convention of having one in a given context, and not out of any expectation that it actually offer any real protection for anything.
As you note, the levy is for private copying. However, thanks to the most recent copyright legislation which was pushed through by our current government, Canadians are now paying that levy for something that they can no longer legally do if the work they wanted to copy utilized any kind of technological protection measure which might prevent it from simply being copied too casually.... since such measures are becoming increasingly prevalent as content increasingly moves towards an all-digital format, the levy will end up being for something that Canadians are no longer practically able to legally do, since the laws regarding TPMs do not contain any exception for private copying (even though the government that proposed the bill before it became law was repeatedly asked to insert such an exception into the bill by its opponents).
Would a person's freedom to go to movies at all end permanently if such technology were implanted directly into their skull? While we're probably still a few years away from that becoming anything even remotely resembling merely uncommon, it's still something that many of us are liable to see happening in our lifetimes
How is complaining prior to them closing the door relevant to people talking on their cell phones while it's in flight, which is the primary subject of this discussion?
If I'm talking to somebody else and you're standing next to me, I'm not forcing you to listen. People with enough to occupy their mind can easily tune out their surroundings.
I'd dare say that a majority of people don't give a shit what most other people do on a plane, as long as it isn't compromising plane safety, since they aren't actually sitting close enough to most of the people who might disturb them to care. Thus, banning them would be a response to a vocal minority. The only reason the majority wouldn't object is because they don't care one way or the other what most of the other people are doing in the first place.
Anyone who resorts to violence over somebody who is simply being annoying has pretty damn serious anger maanagement issues that will land them in jail in a lot of jurisdictions if they actually do so.
So should chatter not be allowed on airplanes either? What is the difference in noise level between somebody talking on a phone and somebody just talking to somebody else?
Bearing in mind that we are on the brink of having self-driving cars now, cars that are capable of self-driving will, for the foreseeable future, still require an attentive driver who can take over driving from the vehicle at any time. While technology changes quickly... habits, mindsets, and what people are ultimately most comfortable with (and in turn, the law) does not. Do you seriously think that at the rate at which society accepts technological change, people, and the laws governing self-driving cars will have already changed to have fully accommodated them before we have reliable brain-computer interfaces that could enable functionality comparable to what Glass can do today, but without wearing anything that may obscure your vision? Sure, we might be a handful of decades away from the latter, but how many more decades are we away from the former?
... these things are wired directly to the brain, and you don't even need to wear anything that obscured your vision? Still a distraction, of course... but is it still "watching a monitor" when it's inside of your own head?
Explain how you can calculate mean deviation without revisiting every data point you collected to see what it originally was. It is my assertion that you cannot.
Explain how you can revisit every element in a red-black tree that has been inserted into it in anything less than O(n) time.
I do not dispute the access time of red-black trees that you've cited, what I am saying is that you apparently don't understand the actual scope of the problem of computing these values to think that such a data structure would even begin to make a program that needs to do something like compute standard deviation more efficiently unless it was implemented absurdly stupidly in the first place.
I repeat, the calculation for standard deviation can be performed in O(1) time from aggregate data that uses O(1) space, which can be collected as you make an initial pass over the data (which is by itself an O(n) operation). Calculating the mean, the standard deviation, and other similar statistics can be directly computed in constant time without having access to the original data points collected, and only the aggregate data..
O(log(n)) for each and every insertion, yes... when you are doing n insertions, that becomes O(n log n). If you are trying to compute the mean deviation at every step as well, you are looking at O(n^2 log n), because you cannot compute the mean deviation without revisiting *every* element you've collected so far, regardless of how they are stored or sorted.
But standard deviation calcuations don't even require that you even insert the data that you are monitoring into a data structure at all... it only requires that you see the data once, and you never need to look at it again, just like the mean calculation, which can be done in O(1). The total time, therefore, including data collection is just O(n), because that's the amount of time required to collect n data points without storing them all... only storing sums of data collected so far. (but with standard deviation, you need to also store the sum of the squares of all the data collected as well).
Collecting the data alone is a log(n) step... and can be worse if you are trying to keep the data sorted while you collect it. How can you calculate the mean deviation at any time without revisiting all of the data points that you have collected so far? How can you calculate do it in any time better than O(n)? Calculating standard deviation takes O(1) and does not require reexamining the data at all if you've been keeping track of right things during data collection (which still takes O(n)).
Incorrect... you need one pass to collect the data, and a second pass to compute the mean deviation. Both passes are O(n). You do not need to do a second pass to compute the standard deviation, it can be calculated in O(1) time based on data collected in the first pass.
If you are only computing this once, doing two O(n)'s is just O(n), but if you are wanting to continually recalculate the mean as you add more elements to your data set, then the difference between them becomes much larger... mean deviation with data collection ends up being quadratic with the amount of data collected, while standard deviation with data collection remains linear with the amount of data collected.
A whole lot faster actually. Mean deviation is O(n) for time and requires that all of the data be stored. Standard deviation calculation is O(1), and does not reequire access to the original data, so it can be used on ephemeral data sources or data streams that are unbounded in size, where the calculation needs to still be made regularly.
Calculating the standard deviation of a data set with only one pass over the data as you initially collect it is fairly straightforward. This is ideal in situations where the data you are working with is ephemeral, or of unbounded size and impractical to store every individual sample. How do you calculate the mean deviation without having to go back and revisit all of your samples?
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Note that no constraints were made about the upper length of the password... only on its contents...and the restriction that I described on contents does not, in general, considerably simplify a brute-force checker (in fact, it would probably tend to complicate it). An 8 character password might be crackable in only a few seconds with today's fastest multicore GPU's, assuming that you knew in advance that it was not more than 8 characters... but without knowing the upper bounds of the domain to search, the problem gets massively more complex.
How about "Create a mixed-case password at least 8 characters long, having at least one upper case letter that is not in the initial position, at least one lower case letter, and at least one digit and one special symbol that are not in either of the final two positions, and which contains no english word that is more than 4 characters"?
...that the decision to use such a password (or perhaps more correctly, the lack of a decision to utilize a good password) would usually just be a response to either a necessity or else a merely common convention of having one in a given context, and not out of any expectation that it actually offer any real protection for anything.
Do you know of a such a service that is available in Canada?
As you note, the levy is for private copying. However, thanks to the most recent copyright legislation which was pushed through by our current government, Canadians are now paying that levy for something that they can no longer legally do if the work they wanted to copy utilized any kind of technological protection measure which might prevent it from simply being copied too casually.... since such measures are becoming increasingly prevalent as content increasingly moves towards an all-digital format, the levy will end up being for something that Canadians are no longer practically able to legally do, since the laws regarding TPMs do not contain any exception for private copying (even though the government that proposed the bill before it became law was repeatedly asked to insert such an exception into the bill by its opponents).
Or... a non-prince charming is with a beautiful woman who should be waaay out of his league who simply loves him.
It's not a rational situation, but it can still definitely be true.
Would a person's freedom to go to movies at all end permanently if such technology were implanted directly into their skull? While we're probably still a few years away from that becoming anything even remotely resembling merely uncommon, it's still something that many of us are liable to see happening in our lifetimes
How is complaining prior to them closing the door relevant to people talking on their cell phones while it's in flight, which is the primary subject of this discussion?
If I'm talking to somebody else and you're standing next to me, I'm not forcing you to listen. People with enough to occupy their mind can easily tune out their surroundings.
If a person refuses to reduce their noise level, yes... they will kick the person out
I'd dare say that a majority of people don't give a shit what most other people do on a plane, as long as it isn't compromising plane safety, since they aren't actually sitting close enough to most of the people who might disturb them to care. Thus, banning them would be a response to a vocal minority. The only reason the majority wouldn't object is because they don't care one way or the other what most of the other people are doing in the first place.
Maybe the ones you go to. Good ones will.
Anyone who resorts to violence over somebody who is simply being annoying has pretty damn serious anger maanagement issues that will land them in jail in a lot of jurisdictions if they actually do so.
How do you propose doing that while the plane is in the air? Or are you suggesting capital punishment without even the benefit of a legal trial?
So should chatter not be allowed on airplanes either? What is the difference in noise level between somebody talking on a phone and somebody just talking to somebody else?
Bearing in mind that we are on the brink of having self-driving cars now, cars that are capable of self-driving will, for the foreseeable future, still require an attentive driver who can take over driving from the vehicle at any time. While technology changes quickly... habits, mindsets, and what people are ultimately most comfortable with (and in turn, the law) does not. Do you seriously think that at the rate at which society accepts technological change, people, and the laws governing self-driving cars will have already changed to have fully accommodated them before we have reliable brain-computer interfaces that could enable functionality comparable to what Glass can do today, but without wearing anything that may obscure your vision? Sure, we might be a handful of decades away from the latter, but how many more decades are we away from the former?
... these things are wired directly to the brain, and you don't even need to wear anything that obscured your vision? Still a distraction, of course... but is it still "watching a monitor" when it's inside of your own head?
Explain how you can calculate mean deviation without revisiting every data point you collected to see what it originally was. It is my assertion that you cannot.
Explain how you can revisit every element in a red-black tree that has been inserted into it in anything less than O(n) time.
I do not dispute the access time of red-black trees that you've cited, what I am saying is that you apparently don't understand the actual scope of the problem of computing these values to think that such a data structure would even begin to make a program that needs to do something like compute standard deviation more efficiently unless it was implemented absurdly stupidly in the first place.
I repeat, the calculation for standard deviation can be performed in O(1) time from aggregate data that uses O(1) space, which can be collected as you make an initial pass over the data (which is by itself an O(n) operation). Calculating the mean, the standard deviation, and other similar statistics can be directly computed in constant time without having access to the original data points collected, and only the aggregate data..
O(log(n)) for each and every insertion, yes... when you are doing n insertions, that becomes O(n log n). If you are trying to compute the mean deviation at every step as well, you are looking at O(n^2 log n), because you cannot compute the mean deviation without revisiting *every* element you've collected so far, regardless of how they are stored or sorted.
But standard deviation calcuations don't even require that you even insert the data that you are monitoring into a data structure at all... it only requires that you see the data once, and you never need to look at it again, just like the mean calculation, which can be done in O(1). The total time, therefore, including data collection is just O(n), because that's the amount of time required to collect n data points without storing them all... only storing sums of data collected so far. (but with standard deviation, you need to also store the sum of the squares of all the data collected as well).
Collecting the data alone is a log(n) step... and can be worse if you are trying to keep the data sorted while you collect it. How can you calculate the mean deviation at any time without revisiting all of the data points that you have collected so far? How can you calculate do it in any time better than O(n)? Calculating standard deviation takes O(1) and does not require reexamining the data at all if you've been keeping track of right things during data collection (which still takes O(n)).
If you are only computing this once, doing two O(n)'s is just O(n), but if you are wanting to continually recalculate the mean as you add more elements to your data set, then the difference between them becomes much larger... mean deviation with data collection ends up being quadratic with the amount of data collected, while standard deviation with data collection remains linear with the amount of data collected.
A whole lot faster actually. Mean deviation is O(n) for time and requires that all of the data be stored. Standard deviation calculation is O(1), and does not reequire access to the original data, so it can be used on ephemeral data sources or data streams that are unbounded in size, where the calculation needs to still be made regularly.
Calculating the standard deviation of a data set with only one pass over the data as you initially collect it is fairly straightforward. This is ideal in situations where the data you are working with is ephemeral, or of unbounded size and impractical to store every individual sample. How do you calculate the mean deviation without having to go back and revisit all of your samples?
A police officer with a warrant would still identify themselves as an officer to anyone who was unsuspecting.
Why would a federal officer, who has not identified himself, break into the guy's house and threaten him or his family with a weapon?