Answer:
D) $320,000
Explanation:
We are given the following information:
- unit price = $25 per frame
- variable costs = $12 per frame
- fixed costs = $50,000 for 25,000 frames or $2 per frame
If Frames is able to sell 30,000 frames in one month, their operating income should be:
Total sales revenue $750,000 (= $25 per frame x 30,000 frames)
<u>COGS -$430,000 [= (30,000 x $12) + $70,000] </u>
Gross operating profit $320,000
<span> the rate of inflation for that year is 10%
To calculate the rate of inflation for that year, we need to use this formula:
Rate of inflation = (CPI2 - CP1) / CPI1
Rate of inflation = (275 - 250) / 250
Rate of inflation = 25 / 250
Rate of inflation = 1 / 10
Rate of inflation = 10 %</span>
Answer:
$0.30 per direct labor-hour
Explanation:
The computation of the variable cost per direct labor is shown below:
Variable cost per direct hour = (High maintenance cost incurred - low maintenance cost incurred) ÷ (High direct labor hours - low direct labor hours)
= ($4,000 - $1,900) ÷ (9,000 hours - 2,000 hours)
= $2,100 ÷ 7,000 hours
= $0.30 per direct labor-hour
Answer:
The correct answer is c) neural network .
Explanation:
Neural networks (also known as connectionist systems) are a computational model vaguely inspired by the behavior observed in their biological counterpart. It consists of a set of units, called artificial neurons, connected to each other to transmit signals. The input information crosses the neural network (where it undergoes various operations) producing output values.
Each neuron is connected to others through links. In these links the output value of the previous neuron is multiplied by a weight value. These weights in the bonds can increase or inhibit the activation state of adjacent neurons. Similarly, at the exit of the neuron, there may be a limiting function or threshold, which modifies the result value or imposes a limit that must be exceeded before spreading to another neuron. This function is known as the activation function. Artificial neural networks (also known as connectionist systems) are a computational model vaguely inspired by the behavior observed in their biological counterpart. It consists of a set of units, called artificial neurons, connected to each other to transmit signals. The input information crosses the neural network (where it undergoes various operations) producing output values.
