@Stretto Okay, you do have a good point there. Since piecewise is a very weak part of Maple, I usually convert to Heaviside form. This can be done automatically, like this:

with(inttrans):
sinc:= x-> piecewise(x=0, 1, sin(Pi*x)/x/Pi):
SE:= unapply(convert(sinc(x)*exp(-x^2), Heaviside), x);
plot(abs(fourier(SE(x),x,s)), s= 0..5)

@acer Your workaround using :-D instead of D doesn't work in Maple 2019. It seems like :-D is inert on the operators overridden by VectorCalculus. And I can't figure out what the overridden D is supposed to do.

restart:
kernelopts(version);
   Maple 2019.0, X86 64 WINDOWS, Mar 9 2019, Build ID 1384062
with(VectorCalculus):
assume(x, real);
assume(y, real);
:-D[1]((x,y)-> x^2-y^2):
lprint(%);
D[1]((x, y) -> VectorCalculus:-`+`(x^2,VectorCalculus:-`-`(y^2)))

I suspect that this is just a formatting command for internal use by the GUI that slipped through the cracks. To test that, check what you get from 

lprint(%);

I know that you're in Japan, and it may be easier for things to "slip through the cracks" in a foreign-language GUI.

@Kitonum I was just about to post my simplify solution, but you beat me to it:

E:= unapply(add((a||i)^k, i= 1..3), k):
simplify(E~([$1..9]), {(E~([1,2,3])=~[1,2,3])[]});

      [1, 2, 3, 25/6, 6, 103/12, 221/18, 1265/72, 905/36]

I suspect that this may use significantly less computational effort than solve followed by eval, although I haven't tested that.

You may have already seen this help page. If not, I think that it may provide a little bit of information that will help you. It's

?ColorTools,ColorSpaces. It specifes the 9 predefined gamuts that Maple has. Each has a link to an external reference (all Wikipedia, I think). Hopefully that means that Maple follows the specs of those external references.

@Simon45 As you yourself said, "the advantage of the Milne method over [RK4] is a higher speed." My guess is that backtracking is done in the hope that future iterations can be avoided. If you set eps lower, you'll see an increase in the number of iterations as measured by the number of actual calls to the derivative evaluator (counted by the trick that I gave). This suggests to me that the method tries to achieve a target accuracy and can forego some iterations if they're not needed. Note that for most methods that use a fixed stepsize (your h), such as RK4, the number of iterations is determined by that stepsize rather than by a tolerance (your eps).

@mimi990 Try separating the symbolic/scalar and Matrix terms and generating Matlab code for them separately.

Your code works perfectly for me in Maple 2019. I get the following plot, which shows that the approximation error is below the limit of visual detection:

What happens when you run it in your Maple?

@mmcdara By "aliasing", do you mean Gibbs phenomenon?

For the problem at hand, I think that it's clear (by default) that the intention is to consider the function as periodic with period 2*Pi in the simplest way: simply with jump discontinuities at 2*Pi*n for all integer n.

Is MVA millivolt-amps? megavolt-amps? What is the r in MVAr?

@mmcdara You need to replace all occurences of point with geometry:-point.

While the geometry package is quite old, and it has significant differences from more-modern packages, I don't see this as one of those differences.

@tizozadoxo I gave a clear method for doing this in Maple. What don't you understand about what I wrote? I'd be happy to give more details.

@Kitonum Oh, I see them now. I overlooked them as dirt on my screen. I guess that they're not supposed to be there.

I tried to answer your question, but I'm confused by the plethora of d-like symbols in your expressions. Do they all represent derivatives/differentials? In particular, what's the lowercase delta?

@jmalik7 Don't confuse FAIL with false. FAIL means that is was neither able to rigorously prove the universally quantified statement (the quantification being with respect to the assumptions on symbolic variables) nor was it able to find a counterexample. Since finding counterexamples (when they exist) is generally easier than proving a universal, FAIL results are more likely to be in reality true rather than false. 

Acer said, "you may receive a result of FAIL from is, which doesn't help." Yes, it doesn't help if you require rigor. But if just knowing what's likely is sufficient, I'd accept FAIL as true. Likewise, a FAIL from coulditbe (the existential quantifier version of is) is likely to be false in reality.