Hector: Alright, explain your game to me, Mr. Hare.
Hare: First, I will stand somewhere along the race track, but I won’t tell you where, and this wall hides me from view. Now, do you see this large contraption here?
Hector: Indeed. There is a 
Hare: Very astute!
Hector: And I suppose that my goal is to trap you under the net?
Hare: Without any information to guide you? No such nonsense. In fact, the game is much more subtle than that. You will indeed crank the net to a position of your choosing — let’s name the end closest to you 
Hector: Too easy! If 
Hare: Ah, not so fast. You see, there are random winds along the direction of the race track in these parts, and so the net may be blown considerably off from a straight downward course.
Hector: Which, of course, I won’t be able to see, due to the wall.
Hare: Precisely.
Hector: So, we could say that the net covers not ![[n, n + l]](http://s.wordpress.com/latex.php?latex=%5Bn%2C%20n%20%2B%20l%5D&bg=ffffff&fg=000000&s=0 "[n, n + l]")
![[u, u + l]](http://s.wordpress.com/latex.php?latex=%5Bu%2C%20u%20%2B%20l%5D&bg=ffffff&fg=000000&s=0 "[u, u + l]")
Hare: If you like.
Hector: Hence the anemometer, from which I can estimate 
Hare: Well played, Hector. But there is still one outstanding consideration.
Hector: And that is?
Hare: Actually computing the probability you speak of quickly enough to make your wager! I have somewhere to be promptly after this game, and as you know, we leporids hate to be late…
And with that, the Hare races off around the wall and down the track.
) gets old very quickly (and saying how you “hate doing this” or “we never do this” doesn’t make it more excusable). Hearing small one-man podcasts repeatedly talk about money gets really irritating. If you’re a big organization that actually has an infrastructure and a following outside of your podcast, this is more excusable, though depending on context it can still be annoying. I think I must have dropped at least 4-5 podcasts because the constant jabbering about money or complaining about the lack of it just got so annoying and eliminated or reduced the usefuless of the podcast. If you talk about money do it minimally, giving listeners the information they need in order to donate (without repeating it too often). While one might pay for audio content, it is highly unlikely anyone wants to pay for audio content of you asking people to pay you for audio content. If you do ask for money, I suggest taking one of the following approaches:
from the image plane to the laser plane in a 
coordinates of a point in the image map through 
coordinates in the laser plane. Then, if 
is the transport direction offset between profiles, the 3D coordinates of such a point in profile 
are 
.
is the key. Assuming the transport direction is positive away from the laser side and the object runs toward the laser, a point 
, where 
and 
are found as before.
matrix representation 
and 
, and supposing 
is the line of intersection of 
between vectors 
and 
lying, respectively, in 
, where the value of each member of the set is an estimated value of the fuzzy number, and the 
-value of the member is its grade.
whereas the the computation of the exponentiation took about the same time in both cases.
Having experienced some ‘weird’ traffic the other day, a client contacted me regarding this problem. One of the datacenters we deal with contacted my client and sent him the following logs from an attack that seems to occured from his server:![\left[\begin{array}{c}1 \\ m\end{array}\right]](http://s.wordpress.com/latex.php?latex=%5Cleft%5B%5Cbegin%7Barray%7D%7Bc%7D1%20%5C%5C%20m%5Cend%7Barray%7D%5Cright%5D&bg=ffffff&fg=000000&s=0 "\left[\begin{array}{c}1 \\ m\end{array}\right]")
![\left[\begin{array}{c}1 \\ m'\end{array}\right]](http://s.wordpress.com/latex.php?latex=%5Cleft%5B%5Cbegin%7Barray%7D%7Bc%7D1%20%5C%5C%20m%27%5Cend%7Barray%7D%5Cright%5D&bg=ffffff&fg=000000&s=0 "\left[\begin{array}{c}1 \\ m'\end{array}\right]")
![\left[\begin{array}{c}1 \\ m'\end{array}\right] = \left[\begin{array}{cc}\cos\theta & -\sin\theta \\ \sin\theta & \cos\theta\end{array}\right] \left[\begin{array}{c}1 \\ m\end{array}\right]](http://s.wordpress.com/latex.php?latex=%5Cleft%5B%5Cbegin%7Barray%7D%7Bc%7D1%20%5C%5C%20m%27%5Cend%7Barray%7D%5Cright%5D%20%3D%20%5Cleft%5B%5Cbegin%7Barray%7D%7Bcc%7D%5Ccos%5Ctheta%20%26%20-%5Csin%5Ctheta%20%5C%5C%20%5Csin%5Ctheta%20%26%20%5Ccos%5Ctheta%5Cend%7Barray%7D%5Cright%5D%20%5Cleft%5B%5Cbegin%7Barray%7D%7Bc%7D1%20%5C%5C%20m%5Cend%7Barray%7D%5Cright%5D&bg=ffffff&fg=000000&s=0 "\left[\begin{array}{c}1 \\ m'\end{array}\right] = \left[\begin{array}{cc}\cos\theta & -\sin\theta \\ \sin\theta & \cos\theta\end{array}\right] \left[\begin{array}{c}1 \\ m\end{array}\right]")
where 
, ![\rho \in [0, \pi]](http://s.wordpress.com/latex.php?latex=%5Crho%20%5Cin%20%5B0%2C%20%5Cpi%5D&bg=ffffff&fg=000000&s=0 "\rho \in [0, \pi]")
, and 
— what is that called? Of course, this generalizes to a (2p – 1)-dimensional space with a p-dimensional Euclidean spatial component. I have been calling fuzzy subsets of this space spatial-directional fuzzy sets, but spatial-directional space sounds patently ridiculous.
In an otherwise generally unremarkable piece in the April 2010 issue of Usenix’s login; magazine (pp. 70-71) listing goofy fake protocols, Robert Ferrell has this gem:
of a set of vertices 
and a set of edged 
; a fuzzy graph (in most definitions) is simply a generalization where 
. However, the complexity seems prohibitive in practice for large camera networks. If we instead move to a discrete representation of the fuzzy coverage model, we can do what I did: make the scene finite, mark a subset of its voxels opaque, then use the voxel traversal of the line from a given point to the principal point of the camera to determine whether it is occluded (i.e. if the traversal includes any opaque voxels).
values of the edges all the way back to the basic parameters of the camera network and the scene (and we know where all the simplifications are). Even better, though, might be something more analytic and general, like using something along the lines of the 
and any positive integer 
:
, and 
, where 
and 
are, respectively, the inclination angle (from the positive 
. How do you tell if the direction 
of such a vector falls inside the exterior half-space defined by the plane normal to 
, it’s dead simple: 
. Doesn’t even matter what 
and 
, there’s no effect on the azimuth, so it’s still pretty straightforward: 
. The 
accounts for the tilt of the plane, and the 
accounts for the azimuth.
, and thus the azimuth angle relative to the plane’s direction of tilt differs from the absolute azimuth angle, it gets a bit trickier. First, we need the magnitude of 
for the 
bit:
, what we want is 
, where 
is the right-handed angle of 
). We could leave it like this, and have the reader calculate 
