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DIA [1.3K]
3 years ago
9

What would be the best command for a student to use to show their work on a math problem?

Computers and Technology
1 answer:
Pepsi [2]3 years ago
5 0

Answer:

A, ink equation

Explanation:

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The capacity of a communication channel is measured in _______.
PSYCHO15rus [73]
<span>The capacity of a communication channel is measured in gb and gps.</span>
4 0
3 years ago
Read 2 more answers
Columns can be added to a page in the page layout tab in the blank grouping
ZanzabumX [31]

Answer:

Page Setup Grouping.

Explanation:

In Microsoft Word, Columns break up the page into, at max, 13 columns, and at minumum, 2. The way you go about doing this is

  1. Go to the Layout Tab
  2. Go to the Page setup Grouping
  3. Click on the Columns Action
  4. In the Dialog Box, choose either from one of the presents, or custom make your own column settings.
  5. Click Okay
  6. Done!

3 0
4 years ago
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Question 2Write a MIPS assembly implementation of the following C/C++ code. Assume small, unsigned integer arithmetic (no range
Licemer1 [7]

Answer:

Please kindly check explainations for the code.

Explanation:

lw $t1, Num1

lw $t2, Num2

lw $t3, Num3

blt $t1, $t2, if

beq $t1, $t2, elseif

else:

add $t0, $t3, 5

sw $t0, Result

endif:

#.....other statements after if-elseif-else

if:

sw $t1, Result

b endif

elseif:

ble $t2, $t3, if2

or $t0, $t1, $t3

sw $t0, Result

b endif

if2:

and $t0, $t2, $t3

sw $t0, Result

b endif

Go to attachment for the onscreen code.

4 0
4 years ago
From a neural network with 11 input variables, one hidden layer with three hidden units, and one output variable, how many param
e-lub [12.9K]

Answer:

40

Explanation:

Given that:

A neural network with 11 input variables possess;

one hidden layer with three hidden units; &

one output variable

For every input, a variable must go to every node.

Thus, we can calculate the weights of weight with respect to connections to input and hidden layer by using the formula:

= ( inputs + bias) × numbers of nodes

= (11 + 1 ) × 3

= 12 × 3

= 36 weights

Also, For one hidden layer (with 3 nodes) and one output

The entry result for every hidden node will go directly to the output

These results will have weights associated with them before computed in the output node.

Thus; using the formula

= (numbers of nodes + bais) output, we get;

= ( 3+ 1 ) × 1

= 4 weights

weights with respect to input and hidden layer total = 36

weights with respect to hidden and output layer total = 4

Finally, the sum of both weights is = 36 + 4

= 40

6 0
3 years ago
Help guys thank you =) ​
MrRissso [65]
1.LR
2.LR
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4.LR
5.HR
6 0
3 years ago
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