xPROBLEM DESCRIPTION:The density of freshwater can be computed as a function oftemperature with the following cubic equation:p = 5.5289x10-³T3 – 8.5016x10-6T² +6.5622x10-5Tc+0.99987=Where p density (g/cm³) vs Tc = temperature (°C). Generate avector of temperatures ranging from 32°F to 93.2°F usingincrements of 3.6°F. Convert this vector to degrees Celsius and thencompute a vector of densities based on the cubic formula. Create aplot of p vs Tc using scilab3:05 D

The answer is : %vector of temperatures FF = 32:3.6:93.2; %convert to celciusT = (5/9) .* ( F-32);…

Answered: x PROBLEM DESCRIPTION: The density of…

Computer Networking: A Top-Down Approach (7th Edition)

7th Edition

ISBN:9780133594140

Author:James Kurose, Keith Ross

Publisher:James Kurose, Keith Ross

Chapter1: Computer Networks And The Internet

Section: Chapter Questions

Problem R1RQ: What is the difference between a host and an end system? List several different types of end...

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In C++, define an integer vector and ask the user to give you values for the vector. Because you used a vector, so you don't need to know the size. user should be able to enter a number until he wants(you can use while loop for termination. for example if the user enters any negative number, but until he enters a positive number, your program should read and push it inside of the vector). the calculate the average of all numbers he entered.
Prompt: In Python language, write a function that applies the logistic sigmoid function to all elements of a NumPy array. Code: import numpy as np import math import matplotlib.pyplot as plt import pandas as pd def sigmoid(inputArray): modifiedArray = np.zeros(len(inputArray)) #YOUR CODE HERE: return(modifiedArray) def test(): inputs = np.arange(-100, 100, 0.5) outputs = sigmoid(inputs) plt.figure(1) plt.plot(inputs) plt.title('Input') plt.xlabel('Index') plt.ylabel('Value') plt.show() plt.figure(2) plt.plot(outputs,'Black') plt.title('Output') plt.xlabel('Index') plt.ylabel('Value') plt.show() test()
Write answer in c++
Question : Imagine that you track your commute times for (10 days) and recorded your observations in minutes as {17, 16, 20, 24, 22, 15, 21, 15, 17, 22}. Enter your observations into a series (vector) in Python and label it 'data'. Next answer the following questions: ● How many times were your commute 20 minutes or more? Hint: Write a condition! What percent of your commutes are less than 17 minutes?
Integers are read from input and stored into a vector until 0 is read. If the vector's last element is odd, output the odd elements in the vector. Otherwise, output the even elements in the vector. End each number with a newline. Ex: If the input is -9 12 -6 1 0, the vector's last element is 1. Thus, the output is: -9 1 Note: (x % 2 != 0) returns true if x is odd. int value; int i; bool isodd; 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 } cin >> value; while (value != 0) { } for (i = 0; i > value; Check return 0; 1 Next level 2 X 1: Compare output 3 4 For input -9 12 -6 1 0, the vector elements are -9, 12, -6, and 1. The last element, 1, is odd. The odd elements in the vector, -9 and 1, are output, each on a new line. Not all tests passed. 2 V 3
Integers are read from input and stored into a vector until 0 is read. If the vector's last element is odd, output the odd elements in the vector. Otherwise, output the even elements in the vector. End each number with a newline. Ex: If the input is -9 12 -6 1 0, the vector's last element is 1. Thus, the output is: -9 1 Note: (x % 2!= 0) returns true if x is odd. 4 5 int main() { 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20} vector vect1; int value; int i; bool isodd; cin >> value; while (value != 0) { vect1.push_back(value); cin >> value; } V* Your code goes here */ return 0; 2 3
import numpy as np import torch import matplotlib.pyplot as plt Quiz Preparation Question 1. Write a function that generates a random tensor of n x n (n is the input). The output is the mean of the tensor. = 2, 4, 8, 16, ... 1024 and generate a vector 2. Write a code (for loop) that call that calls the function above with n = M(n). Plot the vector as a function of the log of n. 3. Given an n x m array write a code that replaces every element that is larger than 0.5 with 0.5. 4. The second derivative of a function can be approximated by the finite difference 1 ƒ"(x₂) = 73 (ƒ(£;+1) — 2ƒ(x;) + f(x;-1)) Given a vector f with values f = [f(xo),..., f(n) write a code that computes the approximation to f"(x) 5. The power method is a method to compute the largest eigenvalue of a matrix. Your google search is using this method every time you perform a google search. The method consists of the iteration Vj+1 = Av; || Avi|| where v; is a vector with chosen as a random vector, and A is the matrix…

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