The answer would be:
<span>It's rate of gaining speed decreases.
The rate at which speed changes is called acceleration,
You can think of this problem as an inclined plane. But the angle of an inclined plane is constantly decreasing.
We know that on a frictionless inclined plane acceleration of an object is:
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<span>Where g is the gravitational acceleration of the Earth and

is the angle of an inclined plane.
Using our analogy, the ball would start on an inclined plane with a 90-degree angle and that angle would continue to decrease to zero.
The sine function is 1 at 90 degrees and is equal to zero at 0 degrees. Since our acceleration is proportional to the sine, and sine function is decreasing with the angle, our acceleration is also decreasing.
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Glucose has a chemical formula of: C6H12O6 That means glucose is made of 6 carbon atoms, 12 hydrogen atoms and
(6 oxygen atoms)
Answer:
532.0725 m
102.17270893 m/s
Explanation:
t = Time taken
u = Initial velocity
v = Final velocity
s = Displacement
a = Acceleration
g = Acceleration due to gravity = 9.81 m/s² = g
H = Height of cliff
Distance traveled in 3 seconds

Distance traveled by sound = 2H-44.145 m

The height of the cliff is 532.0725 m

Her speed just before she hits the ground is 102.17270893 m/s
Answer:
Moon
Explanation:
although the moon is by far the smallest mass of the listed bodies, it is also by far the closest.
Source localization in ocean acoustics is posed as a machine learning problem in which data-driven methods learn source ranges directly from observed acoustic data: True.
<h3>What is machine learning?</h3>
Machine learning (ML) is also known as artificial intelligence (AI) and it can be defined as a subfield in computer science which typically focuses on the use of computer algorithms, data-driven techniques (methods) and technologies to develop a smart computer-controlled robot that has the ability to automatically perform and manage tasks that are exclusively meant for humans or solved by using human intelligence.
In Machine learning (ML), data-driven techniques (methods) are used to learn source ranges directly from observed acoustic data in a bid to proffer solutions to source localization in ocean acoustics.
In conclusion, a normalized sample covariance matrix (SCM) is constructed and used as the input, especially after pre-processing the pressure that's received by a vertical linear array in Machine learning (ML).
Read more on machine learning here: brainly.com/question/25523571
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