the mask is too small but in the movie clip editor its looks good is it because I filmed with an iPhone  I can resize it my self but I want it to be normal
I masked an image in the UV/Image editor masking section. I then used that mask in the compositor for background replacement. However, the mask size seems to be different. Why is that? Here's a screenshot:
How can I give a script its own icon in the Unity launcher? With Ubuntu 16.04, if you create a launcher (desktop file in ~/.local/share/applications) with a custom icon for a terminal application (so with Terminal=true) then when you start it, it will spawn a new standard terminal icon, and your custom icon will pulse and disappear within a few seconds.  In 14.04, it just worked as expected. (it would not start a new standard terminal icon).   Any idea what to do to change this behaviour? I have a few terminal apps that I want to launch from unity and the new behaviour is problematic (I lose trace of which is which since they all end up with the standard terminal icon)... Catenatives followed by infinitives and gerunds using nginx with SNI By now I've not used SNI with nginx yet. But as IP address pools are quite filled and commercial XP support is about to cease (finally) I'm thinking about converting a few sites to SNI.  I'm aware of the general limitations and pitfalls that might come along with SNI (XP issue, very old browsers). But beyond that is there anything I should be aware of?   Like - nginx related pitfalls when using SNI - issues/bugs with recent (notable!) browsers Show the two fields are not isomorphic Let $p,q,r$ be prime integers with $q\neq r$. Let $\sqrt[p]q$ denote any root of $x^p-q$ and $\sqrt[p]r$ denote any root of $x^p-r$. Please show that $\mathbb{Q}(\sqrt[p]q)\neq\mathbb{Q}(\sqrt[p]r)$.  By Eisenstein we know the two polynomials are irreducible and so they are minimal polynomials and both have degree $p$. EM algorithm gaussian mixtures- derivation I'm trying to make sense of a derivation I'm following from the lecture notes of Stanford's ML course.  Specifically the notes are here:   I'm particular I'm interested in the step where they are optimizing the lower bound of the log-likelihood by finding the derivative of that function w.r.t the mean (top of page 7). I'm a bit stuck on going from line 1 to line 2 in that sequence.  To copy here (using abbreviated notation for space):  $$ \nabla \mu_s \sum_{i=1}^{m}\sum_{j=1}^{k} w_j^{(i)}\log\frac{\alpha_j \exp\psi_{j}^{(i)}\phi_j}{w_j^{(i)}}  \qquad(1) $$ $$ \nabla \mu_s \sum_{i=1}^{m}\sum_{j=1}^{k} w_j^{(i)}\psi_{j}^{(i)}\qquad(2) $$ where $\psi_{j}^{(i)} =-\frac{1}{2}(x^{(i)}-\mu_j)^T\Sigma^{-1}_{j}(x^{(i)}-\mu_j)$ and $\alpha_j=\frac{1}{(2\pi)^{n/2}|\Sigma_j|^{1/2}}$.  The quantity $\mu_s$ is the mean (of a multivariate gaussian distribution) for class $s$.    In short, I'm not sure how they get from (1) to (2).  From just changing the log of (1) I see:  $$ \nabla \mu_s \sum_{i=1}^{m}\sum_{j=1}^{k} w_j^{(i)}\log \left(\alpha_j \exp\psi_{j}^{(i)}\phi_j\right) - w_j^{(i)}\log w_j^{(i)} \qquad(1) $$  To get to their form (2) my impression is that they take pre-emptively discard terms that would contain derivatives of $w_j^{(i)}$ (w.r.t. $\mu_s$).  At least if you assume that much, you get to (2).  However, as they show earlier in that PDF,  $$ w_j^{(i)} = p(z^{(i)}=j | x^{(i)}) =\frac{p(x^{(i)}|z^{(i)}=j)p(z^{(i)}=j) }{\sum_j p(x^{(i)},z^{(i)}=j) } $$ i.e. this quantity is the posterior distribution of the class labels.  Intuitively, it seems like $\partial w_j^{(i)}/ \partial \mu_s$ should be non-zero.  After all, changing the location of the mean $\mu_s$ would change your posterior probability for a particular class given the same data.  (Right?).  Just from a mechanical point of view, $\partial w_j^{(i)}/\partial \mu_j$ would seemingly have some non-zero terms since $p(x^{(i)}|z^{(i)}=j) \sim \mathcal{N}(\mu_j, \Sigma_j)$.  If I work through the algebra, I get  $$ \frac{\partial w_j^{(i)}}{\partial \mu_j} = w_j^{(i)}(1-w_j^{(i)})\frac{\partial \psi^{(i)}_{j}}{\partial \mu_j} $$  What am I missing here?  If I take the log-likelihood (without even thinking about EM algorithm),    $$ \ell = \sum_{i=1}^{m}\log \sum_{j=1}^{k}p(x^{(i)}|z^{(i)}=j)p(z^{(i)}=j) $$ and differentiate w.r.t $\mu_s$, I correctly get  $$ \mu_s^* = \frac{\sum_{i=1}^{m}w_s^{(i)}x^{(i)}}{\sum_{i=1}^{m}w_s^{(i)}} $$  so I'm comfortable with the eventual result, just not the intermediate steps. If A is a finite set and B is an infinite set, then B\A is an infinite set Prove: If $A$ is a finite set and $B$ is an infinite set, then $B \setminus A$ is an infinite set.   I've tried proving the contrapositive, that if $B \setminus A$ is a finite set then $A$ is infinite or $B$ is finite, but I don't think this is the way to go. I want to see what nodes exist under a certain domain from within the domain. Short of querying every valid IP address within that domain, is there a way to get all records/map the network? Can I get back my saved data? How can I install firmware-b43-installer driver if I can't connect to internet by wire? Why does part of my model disappear when I zoom in on it in the 3D Viewport? Adding CSS Reference on Site Page What do people who are using a pensieve look like? As far as I remember from the books, there's no description of what a person using a Pensieve looks like. When Harry is using the Pensieve, he describes it as if he were falling into it, but it's never stated whether his body really enters the Pensieve, because the experience is just told from his point of view.   Now let's say Dumbledore enters his office while Harry was using the Pensieve -- what would Dumbledore see? Is there an answer in the books/canon? List of feature engineering techniques Is there any resource with a list of feature engineering techniques? A mapping of type of data, model and feature engineering technique would be a gold mine. Sometimes I have asked a question which got no answers, but is answered in the comments to the question.  How should I handle these questions? I can't accept an answer, so it is never an accepted question.  For example this one:   (ok here the answer in the comments is from me, but nevertheless I also have others of them) Would it be possible to generate the original data from a SHA-512 checksum? So, I have a file that is XY Exabytes big. I create a SHA-512 hash from it.    Are there any theoretical chances that I can retrieve the original data just from the sha512 hash?    Also, are there any better hashes then sha512? Is there an online course in Mathematical Methods for Physics, Covering Matrices and Vector Analysis? I am taking a course in Mathematical Methods for physicsPhysics (Junior Level).   We are working from   > Mathematical Methods for physicists, George B.Arfken .    I just need online resources covering ( Matrices, Determinants, Vector Analysis, Tensors and differential forms and Vector spaces...etc) to study and understand from. Why is a geometric progression called so? Just curious about why geometric progression is called so. Is it related to geometry? Retrieve Windows 8 Product Key from mainboard My new laptop came preinstalled with Windows 8. Naively, as I am, I just formatted the harddrive and installed fine old Ubuntu. Now I want to install Windows 8 for dual boot again, but I have no DVD and do download the ISO one needs a product key. That key is not on the back of the laptop anymore but somewhere on the mainboard.  Is there any way to recover the product key from the mainboard using Ubuntu? Is there any way to attract or repel neutrons? I know that neutrons are neutral and have no charge, but is there any other way to interact with them? Why can't I paste § into a Minecraft command?