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Alik [6]
3 years ago
15

One morning, Jane notices drops of water on the outside of a window. Later in the day, she notices that the drops have disappear

ed. What most likely caused the drops to disappear?
Physics
2 answers:
murzikaleks [220]3 years ago
6 0
What mostly caused the drops too disappear is the sun
melamori03 [73]3 years ago
5 0
Evaporation is when water molecules turn into hot air and go to clouds
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You pull a 70-kg crate at an angle of 30° above the horizontal. If you pull with a force of 600N and the coefficient of kinetic
Alenkinab [10]

Answer:

Explanation:

Force of friction acting on the body = μ mg cosθ

= .4  x 70 x 9.8 x cos30

= 237.63 N

component of weight = mgsinθ

= 70 x 9.8 x sin30

= 343 N  

Net upward force = 600 - mgsinθ - μ mg cosθ

= 600 - 343 - 237.63

= 105.37 N

acceleration in upward direction = 105.37 / 70

= 1.5 m /s²

s = ut + 1/2 a t²

= 0 + .5 x 1.5 x 3²

= 6.75 m .

5 0
3 years ago
A 286-kg motorcycle is accelerating up along a ramp that is inclined 31.6° above the horizontal. The propulsion force pushing th
kkurt [141]

Answer:

The acceleration motorcycle

a = 5.13 m / s²

Explanation:

Now to determine the acceleration of the motorcycle

Use the force to analysis motion

∑ F = m * a

∑ F = E - D - m*g * sin ( β ) = m * a

E = 3168 N

D = 230 N

β = 31.6 °

3168 N - 230 N - 286 kg * 9.8 m / s² * sin ( 31.6° ) = 286 kg * a

Now solve to a'

a = [ 3168 N - 230 N - 286 kg * 9.8  m / s² * sin ( 31.6° ) ] / (286 kg)

a = 5.13 m / s²

7 0
3 years ago
Source localization in ocean acoustics is posed as a machine learning problem in which data-driven methods learn source ranges d
Temka [501]

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

#SPJ1

6 0
2 years ago
The natural pH of rain water is?
SOVA2 [1]
5.6 which would be acidic!
6 0
3 years ago
Read 2 more answers
Physics. Need help. Brainlieast answer for most/ all of the answers answered
Mumz [18]

<u>ALL of the following work assumes NO AIR RESISTANCE:</u>

1). an object moving under the influence of only gravity, and not in orbit;  its horizontal velocity is constant, and its vertical motion is accelerated downward at 9.8 m/s²

2). a parabola

3). Horizontal: velocity is constant, acceleration is zero. . . . Vertical: acceleration is 9.8 m/s² downward, velocity depends on whether it was launched, thrown up, thrown down, dropped, etc.

4). a). the one that was thrown horizontally; b). both  hit the ground at the same time; c). both hit the ground with the same vertical velocity

5). a). zero; b). zero; c). gravity ... 9.8 m/s² down; d). 3.06 seconds; e). 4.38 m/s; f). 30 m/s g). no; gravity has no effect on horizontal motion

6). a). 1.8 seconds;   b). 13.1 meters;   c). 17.6 m/s down;   d). 7.3 m/s; gravity has no effect on horizontal motion

7). 45 m/s

8). without air resistance, the ball is traveling horizontally at 13 km/hr, and it lands back in your hand

9). a). 4.49 m/s;  b). 29.7 m/s

10). 7.24 meters

11).  700 meters

12).  A). 103.7 meters ( ! she's in big trouble ! );     B).  17.5 meters

3 0
3 years ago
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