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Serggg [28]
3 years ago
6

Yasir is trying to build an energy-efficient wall and deciding what materials to use. How can he calculate the thermal resistanc

e of the wall?
A. It's the mean layer thermal resistance.
B. It's equal to the least thermally resistant layer.
C. Add the thermal resistance of its layers.
D. Measure the thermal loss.
Engineering
1 answer:
777dan777 [17]3 years ago
8 0

Answer:

Add the thermal R values of each wall layer.

Explanation:

Fiberglass insulation R value, sheetrock, sheathing, siding etc.  All sum together to one composite opposition to heat transfer/loss.

Q= U x A x Delta T

Q= heat transfer btuh

U= 1/R inverse of resistance

A= area of surface

Delta T is temerature difference across the wall.

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Arlecino [84]

The Steps my friend need to make an ethical decision are:

  • Step One: He or she needs to define the Problem.
  • Step Two: He or she needs to find out possible Resources to solve the problem and then  Brainstorm on the  List for the Potential Solutions to the problem.
  • Step Three : Evaluate and examine those Alternatives. ...
  • Step Four : Make his or her Decision, Implement It and then examine your Decision.

<h3>What is ethical decision model?</h3>

An ethical decision-making model is known to be a kind of a tool that can be used by a person to help create the ability to think in regards to an ethical dilemma and come to an ethical decision.

Note that Ethical decision-making is one that is dependent on the key character values such as trustworthiness, respect, role, fairness,  and others.

Therefore, The Steps my friend need to make an ethical decision are:

  • Step One: He or she needs to define the Problem.
  • Step Two: He or she needs to find out possible Resources to solve the problem and then  Brainstorm on the  List for the Potential Solutions to the problem.
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7 0
1 year ago
java Write a program that simulates tossing a coin. Prompt the user for how many times to toss the coin. Code a method with no p
max2010maxim [7]

Answer:

The solution code is written in Java.

  1. public class Main {
  2.    public static void main(String[] args) {
  3.        Scanner inNum = new Scanner(System.in);
  4.        System.out.print("Enter number of toss: ");
  5.        int num = inNum.nextInt();
  6.        for(int i=0; i < num; i++){
  7.            System.out.println(toss());
  8.        }
  9.    }
  10.    public static String toss(){
  11.        String option[] = {"heads", "tails"};
  12.        Random rand = new Random();
  13.        return option[rand.nextInt(2)];
  14.    }
  15. }

Explanation:

Firstly, we create a function <em>toss()</em> with no parameter but will return a string (Line 14). Within the function body, create an option array with two elements, "heads" and "tails" (Line 15). Next create a Random object (Line 16) and use <em>nextInt()</em> method to get random value either 0 or 1. Please note we need to pass the value of 2 into <em>nextInx() </em>method to ensure the random value generated is either 0 or 1.  We use this generate random value as an index of <em>option </em>array and return either "heads" or "tails" as output (Line 17).

In the main program, we create Scanner object and use it to prompt user to input an number for how many times to toss the coin (Line 6 - 7). Next, we use the input num to control how many times a for loop should run (Line 9). In each round of the loop, call the function <em>toss() </em>and print the output to terminal (Line 10).  

4 0
3 years ago
Read 2 more answers
A continuous random variable, X, whose probability density function is given by f(x) = ( λe−λx , if x ≥ 0 0, otherwise is said t
Ganezh [65]

Answer:

a) F(x) = \lambda \int_0^{\infty} e^{-\lambda x} dx= -e^{-\lambda x} \Big|_0^{\infty} = 1- e^{-\lambda x} \

b) P(10 < X

Explanation:

Previous concepts

The cumulative distribution function (CDF) F(x),"describes the probability that a random variableX with a given probability distribution will be found at a value less than or equal to x".

The exponential distribution is "the probability distribution of the time between events in a Poisson process (a process in which events occur continuously and independently at a constant average rate). It is a particular case of the gamma distribution".

Part a

Let X the random variable of interest. We know on this case that X\sim Exp(\lambda)

And we know the probability denisty function for x given by:

f(x) = \lambda e^{-\lambda x} , x\geq 0

In order to find the cdf we need to do the following integral:

F(x) = \lambda \int_0^{\infty} e^{-\lambda x} dx= -e^{-\lambda x} \Big|_0^{\infty} = 1- e^{-\lambda x} \

Part b

Assuming that X \sim Exp(\lambda =0.1), then the density function is given by:

f(x) = 0.1 e^{-0.1 x} dx , x\geq 0

And for this case we want this probability:

P(10 < X

And evaluating the integral we got:

P(10 < X

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