## Algorithms – Understand the linear acceleration set and how strong it is

The linear acceleration set says this for every constant $$c$$You can choose the language $$c$$ faster It does not mean that you can make it faster by a non-constant function.

The acceleration set works by defining a new Turing machine that writes $$c$$ Character of the old Turing machine in a single tape cell, and customize the transient function to simulate in a single step everything that the original machine did between entering and leaving the individual $$c$$-Zeichenblock. If $$c$$ Since this is a constant, it does not depend on the input. You only have to calculate the new machine once and use it for the input you want. But if you want $$c$$ To have a non-constant function, you have to find out what the new machine is each time you run it. This takes an exponentially long time because exponentially many are possible $$c$$Token blocks for which you need to find out the transfer function.

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## Windows 7 – Disable the annoying acceleration for the volume keys

I have volume keys on my keyboard to increase or decrease the volume. This ad will appear when I change the volume: https://i.imgur.com/9EGglRq.png

Each key changes the volume by 2% per single press. If I press the raise key ten times quickly, the volume will increase by 20%. But as far as the removal of the button is concerned – I have reduced the volume by 50%! It starts slowly, at 2% per 1 press, but eventually the percentage rises above 10% per single press. I wanted to reduce the volume by about 20%, but got too low a sound or was even muted. Now it gets very annoying for me!

Does anyone know how to lower the volume when the acceleration decreases?

## android studio – Emulator: Emulator: ERROR: The x86 emulation currently requires hardware acceleration! and Emulator: Operation terminated with exit code 1

I can not virtualize my mobile devices in Android Studio

https://stackoverflow.com/questions/29136173/emulator-error-x86-emulation-currently-erquires-hardware-acceleration

The first was to see if the hardware acceleration was installed and so it was

2) I went to the SDK directory C: Users % USERNAME% AppData Local Android sdk extras intel Hardware_Accelerated_Execution_Manager and run the file intelhaxm-android.exe

but it tells me that virtualization is disabled

Virtualization appears activated

If someone can help me, I would appreciate it very much. I just bought a new computer with an Intel processor and was very excited because I thought it would be easy to virtualize

## Startup acceleration Ubuntu 18.04

I also have the same issue that I have been looking for a lot, but I can find anything to fix it (I have processor = Intel Core i3, RAM = 4G, Swap = 9G) and my boot info is:

```~\$ systemd analysis
Startup completed in 10.299s (kernel) + 49.706s (user space) = 1min 6ms
graphics.target reached 49,694s in user space
```

and graphical analysis

```~\$ systemd-analysis critical-chain graphical.target
The time after activating or starting the device is printed after the "@" mark.
The time taken for the device to start up is printed after the "+" sign.

graphical.target @ 49.694s
Ultmulti-user.target @ 49.693s
└─mysql.service @ 39.610s + 10.082s
Worknetwork.target @ 39.607s
└─wpa_supplicant.service @ 34.142s + 5.464s
└─dbus.service @ 28.807s
└─Basic.target @ 28.749s
└─sockets.target @ 28.749s
└─snapd.socket @ 28,747s + 1 ms
└─sysinit.target @ 28.719s
└─systemd-timesyncd.service @ 28.477s + 240ms
└─systemd-tmpfiles-setup.service @ 27.622s + 716ms
└─systemd-journal-flush.service @ 5,195s + 22,426s
└─systemd-remount-fs.service @ 4.389s + 803ms
└─systemd-journald.socket @ 4.354s
└─system.slice @ 4.354s
└─-.slice @ 4.334s
```

## Time complexity – Definition of acceleration for Amdahl's law

Suppose I have an algorithm C that runs in time T, which decomposes into two "subalgorithms" A and B that run in time p * T and (1-p).T, so the algorithm C needs the time pT + (1-p) * T.

Suppose I have another algorithm C & # 39; that calculates the same thing as the algorithm C that is in time T & # 39; running, where two sub-algorithms A & # 39; and B & # 39; Similar to A and B s.t. p & # 39; * T & # 39; + (1-p & # 39;) * T & # 39; = T & # 39;

I would like to measure the "partial acceleration" of the p-part A of C as in Amdahl's law. Must I

1. have the subalgorithm A & # 39; to compute exactly the same as A or
2. can I have another subalgorithm A & # 39; that computes more than A.

In Case 2, can I still use the ratio of execution times from A to A? As acceleration with ratio p?

Suppose I can not do 1. because I do not have such a subalgorithm A # 2. How can I then measure the execution times of A & # 39; and A if p and p are different?

## Differential Calculation – Calculate the distance at time & # 39; t & # 39; at acceleration and starting point. elastic

Ok, let's imagine we have a rubber band sling and the distance $$d = 0$$ is in the middle of this slingshot.

I'm trying to get a distance equation so I can program the distance timed $$t$$,

A bit like this slingshot, as it's narrow in the middle
Slingshot with a solid band

To my knowledge, the elastic potential energy is

$$e = Kd ^ 2$$

From where $$K$$ is the elasticity and $$d$$ is the distance.

So I think that my acceleration is really straight at any time
(I'm only interested in vertical acceleration):

$$A = -1 * sgn (d) * Kd ^ 2$$

On this basis, however, I have no idea how I can create a distance function or if it is even possible.

Because my last step is that I can really only determine that initial velocity 2 points given (1 possibly $$-d$$ and 1 $$+ d$$) and their times in every place.

I would like some hints on how to solve the above problem or if I am doing it right.

Many Thanks! 🙂

TO EDIT

How can I even calculate the integral of this acceleration function if someone could show that this would be fantastic?

## Performance Optimization – Acceleration of DimensionReduce

I'm interested in accelerating DimensionReduce with the "TSNE" method. I have a matrix with a size of 30000 * 10 and would like to reduce to 30000 * 8. But the calculation is very slow, all suggestions on how to speed up the calculation. Currently I do it the following way:

``````Data = {{0.0136704, 868., 5th, 0th, 0th, 0th, 0.0679724, 1.02337, 5th,
2391.}, {0.0327273, 65., 0., 0., 0., 0., 0.0615385, 1.02337, 5.,
2391.}, {0.0343137, 45., 2., 0., 0., 0., 0.0888889, 0.976633, 3.,
2388.}, {0.0425656, 358., 11, 0.0333333, 0, 0, 0.0642458,
0.976633, 3., 2375.}, {0.0146471, 168., 4., 0.4, 0, 0, 0.0892857,
1,02337, 5, 2378.}, {0,0255665, 362., 6, 0,0833333, 0, 0.
0.0856354, 1.02337, 5, 2368.}, {0.0215647, 443, 5, 0.0967742, 0.
0, 0.0857788, 1.02337, 5, 2377.}, {0.0242424, 435, 6,
0.0294118, 0, 0, 0.110345, 0.976633, 3., 2362.}, {0.0311943, 511.
22., 0., 0., 0., 0.129159, 1.02337, 5. 2360.}, {0.030086, 171.
4., 0., 0., 0., 0.122807, 1.02337, 5., 2361.}, {0.0324948, 222.
10., 0., 0., 0., 0.103604, 0.976633, 3. 2364.}, {0.0232975, 120.
2nd, 0th, 0th, 0th, 0.108333, 1.02337, 5th, 2380th}, {0.046616, 632th, 20th,
0, 0, 0, 0.056962, 1.02337, 5, 2354.}, {0,0187225, 381, 9.
0, 0, 0, 0.0603675, 1.02337, 5, 2342.}, {0,0234043, 421, 11.
0.133333, 0.10, 0.109264, 1.02337, 5, 2384.}, {0.0255072, 375.
8., 0., 0., 0., 0.0906667, 1.02337, 5., 2359.}, {0.0284264, 240.
15., 0.125, 0., 0., 0.129167, 1.02337, 5. 2344.}, {0.0246575, 183.
5., 0., 0., 0., 0.0819672, 1.02337, 5., 2361.}, {0.0155535, 251.
4., 0., 0., 0., 0.0876494, 0.0233665, 4., 2351.}, {0.0232186, 276.
10th, 0th, 0th, 0th, 0.0688406, 1.02337, 5th, 2346th}}

DimensionReduce[data, 8, Method -> {"TSNE", "Perplexity" -> 50},
TargetDevice -> "GPU",
PerformanceGoal -> "Speed"]; // Absolute timing

{0.290914, zero}

DimensionReduce[data, 8, Method -> {"TSNE", "Perplexity" -> 50},
PerformanceGoal -> "Speed"]; // Absolute timing

{0.307318, zero}
``````

## mp.mathematical physics – time to speed determination = & # 39; x & # 39; with changing acceleration?

A roulette ball turns around an edge.

What is the time (t) in which the velocity of the sphere = v (regardless of the number)?

The ball's delay of 4 spins was plotted on a scatter and best described with the following 3rd order polynomial:

A (t) = 0.0396t³ – 1.1035t² + 10.25t -33.898
with R² = 84.6%

I tried to find time and distance from speed and acceleration by:
(Final speed – initial speed) / (acceleration)
Unfortunately, this equation assumes a constant acceleration and is therefore nonsense to me because the acceleration of the ball is not constant.

I do not know if that will be useful, but the relationship I see is:
The higher the ball speed, the higher the deceleration rate.
So I've shown acceleration as a function of speed:

A (V) = -0.00008v3 + 0.0125v2 – 0.7688v + 14.983
R² = 0.88

Many Thanks