Answer:
it allows them to work more efficiently, with fewer waisted resources
Explanation:
<span>Olfactory memory tends to be the most durable. Surprisingly, smells tend to be the most strongly related with memories. This has been shown by people being able to associate smells with events for longer periods than any other sensory input. Most other inputs only stay in memory for a period of milliseconds, up to 2-4 seconds at the most.</span>
Answer:
VoIP gateway
Explanation:
A VoIP stands for the voice over IP. The VoIP gateway is defined as a hardware device which is used to convert the telephony traffic into the packets of data that is used for transmission over the internet. It acts as the bridge and connects the VoIP with the worlds of the legacy telephony.
In a VoIP setup, the signals form the analog phone of the campus equipment are converted to the IP data which can travel over the analog telephone lines of the phone company.
Answer:
D. Mass production
Explanation:
Henry Ford came up with the first assembly line for the production of cars. It was his aim to be able to produce enough cars to meet the high demands. With the assembly line, he was able to produce automobiles more efficiently, lessening the time substantially, to produce a single automobile.
This allowed them to not only produce more automobiles, but also allowed him to maintain the low cost of the car. Being able to produce more automobiles also enabled him to increase his worker's wages.
Answer:
Two examples of processes for data collection are:
In-person interviewing: This is a face-to-face method or process of data collection. It has a high rate of response and allows you to ask follow-up questions when the response of the interviewee is not clear.
Sample Surveys: In this method, a sample is selected from a large population and then a questionnaire is constructed and sent to the sample for them to give their feedback or response in line with the research problem.
Three Key Principles considered in these processes to ensure data accuracy are:
Completeness: This means that what was expected to be collected as data was what was collected. Completeness of data is a vital factor for data quality.
Consistency: There must be uniformity in the data collection process. Everyone involved in the data collection process must understand what is required of them.
Accuracy: The data must be free of errors
Explanation:
