This is a newbie question. I read that JVM's execution starts from searching for the methodname from lowest class in the hierarchy and if the method is not available in that class it traverses to the parent class looking for the method.  If this is the case then why do we need to use "@override" for adding custom logic to the inherited class ?  The below example illustrates my question  class superclassA {  method() { }  }  class subclassB extends superclassA {  @Override  //While executing if JVM starts looking for the method name from the lowest hierarchy //then why do we have to use "override" as the methodname will be matched from the lowest level itself? method()  { --custom subclass specific code... }   }
What are the best practices for using Java's @Override annotation and why?     It seems like it would be overkill to mark every single overridden method with the @Override annotation.   Are there certain programming situations that call for using the @Override and others that should never use the @Override?
Commandline shortcut for current directory similar to ~ for home directory? I upgraded from 17.04 to 17.10 on a Lenovo T540p which has broken two finger touchpad scrolling and right clicking Trackpad two finger scrolling and right-click issue with Ubuntu 17.10 (i386, 64bit, GNOME 3.26.1) on a Lenovo T540p (the model with a Intel Core i5-4210M Haswell CPU etc) How can edge rings be selected in a predictable way? When trying to select multiple edge-rings Shift-Alt-RMB sometimes loops get selected in the one (green) way or the other (red) way.  I couldn't derive a general rule.   How can two or more face-rings following one direction be selected ?  (Easy to reproduce with a default torus mesh.) Proof of Heron's Formula for the area of a triangle Let $a,b,c$ be the lengths of the sides of a triangle. The area is given by Heron's formula: $$A = \sqrt{p(p-a)(p-b)(p-c)},$$ where $p$ is half the perimeter, or $p=\frac{a+b+c}{2}$.  Could you please provide the proof of this formula? Thank you in advance. I've been trying to find this darn series of books for ages, I read them back in early 2001-02 and can't really remember much of them. I think there were 10-ish books, it was an easy read but a long series. On early publications, the covers, were mainly yellow, with small pictures of whatever happens in that book.  The book began with two siblings, a brother and a sister, running in a forest. She conjures up what can only be remembered as a golem type creature. He then uses a high magic 'blast' and wipes out the golem, knackering himself. His sister laughs at him for being 'powerful' but expending himself too much on one big magic blast. The beginning I remember vividly, the rest, not so much.  The story continues as a conflict happens, I believe two worlds are involved? The brother and sister are split up, but this is where my memory becomes vague.  The mechanics of the world seems that there are gems, or stones, set in the backbone, which in turn give access to magic. When the person uses them, they can draw too much, which ends up exhausting them. The 'big bad evil king' kills their father, and destroys their farm early on in the story. What is the difference between a predicate and function? I need to to understand the difference between predicates and functions in the context of Clasual Form Logic in order to define the Herbrand universe.  If I have p(x) :- q(f(x)) would I be right in saying that p and q are predicates while f is a function because it is "nested"?  By this thinking then if I have p(x) :- q(x) both p and q are predicates and I have no functions?  If this is incorrect then how can I tell the difference between a predicate and function? I have located where the error message originates from it is in  line number 221. As I have only a single nvidia driver installed I suspect it is is the same issue. I am not a developer but looking at the code preceding this line I can see the statement.  const char *glob_pattern = "/usr/lib/nvidia-[1-9][0-9][0-9]"  this will pick up nvidia-352/ nvidia-361/ and nvidia-361-prime/ ? on my PC. Is there a reason why "gn" in "reigning" is pronounced /n/ while in "regnant" it is pronounced [gn]? Both reigning and regnant are related to the same Latin noun, regnum.  Why is the ‹gn› spelling pronounced [n] in the first word but [gn] in the second? Python Referenced For Loop How do I bake/add material colors onto my UVmap? I looked everywhere from tutorials to documents and either they only talk about texturing or they are doing the tutorial in 'blender render' when I need it in 'cycles render'.   I have a cube that is toon shaded red. And as you can see it is unwrapped to show the map.    Now I would like to add the color that's on the cube onto the map.   As you can see at the bottom of the image that I created a new image called 'untitled'. Now the next step of baking the colors onto the map is where I become lost. Regardless of which 'Bake Type' that I used, I keep getting error messages like: No valid selected objects.  Everything looks selected to me. No, I am not new to Blender but I am new to color baking. Thank you for any help provided; I used a simple cube first before using other models I already created. Gradient steepest direction and normal to surface? From this , I now understand the gradient to be the directional derivative that returns the steepest slope at a point. However, reading my textbooks, they all say that the gradient is normal to the tangent plane. In the above SE question, the gradient sounds like it should be parallel to a direction in the $xy$ plane, not actually up on the surface.   My question is therefore do I have a misunderstanding of the tangent plane, gradient or directional derivative?   In addition, I question how the gradient always passes through the origin or the $xy$ plane? If for instance in the graphic, the gradient had been another direction (say horizontal), then it wouldn't pass through the origin! In addition, the gradient of other points in the graphic would satisfy this example. Many thanks! I understand that the Bernoulli effect is a flawed explanation for the cause of lift, and does not cause much at all, but how much?   Is there any experimental data on the force caused by the Bernoulli effect? Maybe implicitly through data of the pressure difference between the top and underside of an aeroplane's wings. After that, I assume I could (crudely approximating the pressure to be acting perpendicularly to the flight direction) use $\Delta P A$ to work out the net force on the plane.    Perhaps there is another way to quantitatively analyse the extent to which the Bernoulli effect causes lift.  Edit: see  short cartoon (content similar to Mike Dunlavey's answer). How do I deal with 'sudoers.so must be only be writable by owner'? Whenever I try to install or remove something using terminal it gives the following error message:  bluebird@bluebird:~$ sudo apt-get update sudo: /usr/lib/sudo/sudoers.so must be only be writable by owner sudo: fatal error, unable to load plugins bluebird@bluebird:~$ sudo apt-get remove vlc sudo: /usr/lib/sudo/sudoers.so must be only be writable by owner sudo: fatal error, unable to load plugins bluebird@bluebird:~$ sudo apt-get install apt-file sudo: /usr/lib/sudo/sudoers.so must be only be writable by owner sudo: fatal error, unable to load plugins How to connect to my web server? I have implemented a simple web server as a solution to a course assignment and I want to connect to this web server over the internet. I've set it up to listen on port 22881 and configured my router accordingly as the screenshot below shows    I'm able to connect to my web server locally using http://localhost:22881 and I can connect to the router's interface when I visit http://my.external.ip, but I can't connect to my web server using http://my.external.ip:22881 (I get a connection timeout). Any idea of what may be the problem?  Thanks in advance! I found this confusing when I use the neural network toolbox in Matlab. It divided the raw data set into three parts:   training set validation set test set   I notice in many training or learning algorithm, the data is often divided into 2 parts, the training set and the test set.  My questions are:   what is the difference between validation set and test set?  Is the validation set really specific to neural network? Or it is optional. To go further, is there a difference between validation and testing in context of machine learning? "User accounts" or "users account" Let $\theta \in R^{n}$. The Fisher Information Matrix is defined as:  $$I(\theta)_{i,j} = -E\left[\frac{\partial^{2} \log(f(X|\theta))}{\partial \theta_{i} \partial \theta_{j}}\bigg|\theta\right]$$  How can I prove the Fisher Information Matrix is positive semidefinite? I am being driven crazy by the fact that my media keys aren't working for iTunes. Such a pain! How can I fix this? I've tried the whole Chrome Extensions thing, that being I deleted all my extensions. Still, nothing has fixed this. Thanks to all who reply! How do I derive the Lorentz contraction from the invariant interval? Reviewing some basic special relativity, and I stumbled upon this problem:  From the definition of the proper time: $$c^2d\tau^2=c^2dt^2-dx^2$$ I was able to derive the time dilation formula by using $x=vt$: $$c^2d\tau^2=c^2dt^2-v^2dt^2=c^2dt^2\left(1-\frac{v^2}{c^2}\right)\rightarrow d\tau = dt\sqrt{1-\frac{v^2}{c^2}}=t/\gamma$$  Now, I would very much like to be able to derive the length contraction formula in a similar fashion, and feel strongly that this should be possible. The definition of the invariant interval is: $$ds^2=dx^2-c^2dt^2$$ using $t=\frac{x}{v}$ I tried: $$ds^2=dx^2-\frac{c^2}{v^2}dx^2=dx^2\left(1-\frac{c^2}{v^2}\right)\rightarrow ds=dx\sqrt{1-\frac{c^2}{v^2}}$$  This is where I'm stuck: I don't see how this can be converted to a Lorentz factor...  Any help that will allow me to arrive at the desired result $ds=\gamma dx$ would be very much appreciated. I've seen the identity $\displaystyle \sum_{i \mathop = 0}^n \binom n i^2 = \binom {2 n} n$ used here recently.  I checked for proofs here   I couldn't have figured out the combinatorial proof by myself, and the inductive proof assumes you already know the answer...  So my question is : do you know how to prove directly through computation that $\displaystyle \sum_{i \mathop = 0}^n \binom n i^2 = \binom {2 n} n$ ?