Answer:
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Explanation:
Answer:
The required rated input apparent power is 14.98 HP
Explanation:
Real power input = real power output ÷ efficiency
real power output = 12 HP
efficiency = 90% = 0.9
Real power input = 12 ÷ 0.9 = 13.33 HP
Apparent power input = real power input ÷ power factor = 13.33 ÷ 0.89 = 14.98 HP
Humanistic perspective. A psychological standpoint that focusses on the originality of the individual and believe that human beings possess an innate inclination to improve and to confine their lives through the decisions they make. Sometimes named the "third force" in psychology.
<h3>What does the humanistic perspective focus on?</h3>
Humanistic psychology is a philosophy that emphasizes looking at the whole individual and highlights concepts such as free will, self-efficacy, and self-actualization. Rather than focusing on dysfunction, humanistic psychology aims to help people fulfill their possibility and maximize their well-being.
<h3>What is humanistic standpoint human personality?</h3>
The humanistic perspective on character emphasizes the individualized grades of optimal well-being and the use of creative potential to help others, as well as the relational conditions that promote those grades as the outcomes of healthy development.
To learn more about humanistic perspective, refer
brainly.com/question/28192990
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Answer:
import numpy as np
import time
def matrixMul(m1,m2):
if m1.shape[1] == m2.shape[0]:
t1 = time.time()
r1 = np.zeros((m1.shape[0],m2.shape[1]))
for i in range(m1.shape[0]):
for j in range(m2.shape[1]):
r1[i,j] = (m1[i]*m2.transpose()[j]).sum()
t2 = time.time()
print("Native implementation: ",r1)
print("Time: ",t2-t1)
t1 = time.time()
r2 = m1.dot(m2)
t2 = time.time()
print("\nEfficient implementation: ",r2)
print("Time: ",t2-t1)
else:
print("Wrong dimensions!")
Explanation:
We define a function (matrixMul) that receive two arrays representing the two matrices to be multiplied, then we verify is the dimensions are appropriated for matrix multiplication if so we proceed with the native implementation consisting of two for-loops and prints the result of the operation and the execution time, then we proceed with the efficient implementation using .dot method then we return the result with the operation time. As you can see from the image the execution time is appreciable just for large matrices, in such a case the execution time of the efficient implementation can be 1000 times faster than the native implementation.