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atroni [7]
2 years ago
11

A URL suffix is called a domain name.

Computers and Technology
1 answer:
Marta_Voda [28]2 years ago
5 0
<span>A URL suffix is called a domain name. This statement is False.
</span>URL or Universal Resource Locator is just the same as the domain name. The URL suffix or the domain name suffix is known as the Generic Top-Level Domain (gTLD). It describes the type of organization a website is. Like for example '.org', '.gov', '.edu'
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What are some catchy names for computer basics that you would put on a childrens poster?
Triss [41]

Answer:

not sure

Explanation:

6 0
3 years ago
Write a function DrivingCost with input parameters drivenMiles, milesPerGallon, and dollarsPerGallon, that returns the dollar co
jolli1 [7]

Answer:

the brainly thing is saying that i can't put the answer so i screenshotted it and put it down below

Explanation:

4 0
1 year ago
A signal travels from point A to point B. At point A, the signal power is 100 W. At point B, the power is 90 W. What is the atte
11Alexandr11 [23.1K]

Answer:

Attenuation = 0.458\ db

Explanation:

Given

Power at point A = 100W

Power at point B = 90W

Required

Determine the attenuation in decibels

Attenuation is calculated using the following formula

Attenuation = 10Log_{10}\frac{P_s}{P_d}

Where P_s = Power\ Input and P_d  = Power\ output

P_s = 100W

P_d = 90W

Substitute these values in the given formula

Attenuation = 10Log_{10}\frac{P_s}{P_d}

Attenuation = 10Log_{10}\frac{100}{90}

Attenuation = 10 * 0.04575749056

Attenuation = 0.4575749056

Attenuation = 0.458\ db <em>(Approximated)</em>

7 0
3 years ago
In Broadbent's filter model of attention, the stages of information processing occur in which order?
victus00 [196]

Answer:SENSORY STORE, FILTER, DETECTOR, STM.

Explanation:Donald Broadbent in 1958 stated one of the earliest theory of attention,he stated that physical features of messages are used to select one message for further processing and that all others are lost.This differs from inattentional blindness, which is when you focus hard on something and fail to notice unexpected things entering your visual area. He believes that

Information from all of the stimuli presented at any given time enters a sensory buffer with unlimited capacity.

3 0
3 years ago
A computing company is running a set of processes every day. Each process has its own start time and finish time, during which i
Helga [31]

Answer:

Above all else, let us show that this issue has the greedy choice property.

This implies that worldwide ideal arrangement can be gotten by choosing local ideal arrangements. Presently notice the following:

The global optimal solution of the issue requests us to track down the minimum number of times process_check module should be run.

It is likewise referenced that during each running interaction, process_check module should be called atleast once. Along these lines, the minimum possible number of process_check calls happens when process_check is made close to the quantity of the processes that are run.

Along these lines, we see that the global optimal solution is shaped by choosing optimal answer for the nearby advances.

Along these lines, the issue shows greedy choice property. Thus, we can utilize a greedy algorithm for this issue.

The greedy step in this calculation is to postpone the process_check as far as might be feasible. Thus, it should be run towards the finish of each interaction. So the following algorithm can be utilized:

Sort the cycles by utilizing the completion times.

Towards the finish of the 1st process in the arranged list, run the process_check module. Right now any process that is now running is removed the arranged rundown. The main interaction is additionally removed from the sorted list.

Now repeat stage 2, till all processes are finished.

In the above mentioned algorithm, the costliest advance is the step of sorting. By utilizing the optimal sorting algorithm, for example, merge sort, we can achieve it in O(n log n) asymptotic time.

Along these lines, this greedy algorithm additionally takes O(n log n) asymptotic time complexity.

5 0
2 years ago
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