Answer:
The program is given below with appropriate comments for better understanding
Explanation:
1) LMC Program:
LDA A //Load A
SUB B //Subtract from A, B which is 0.
SKZ // skip next statement if A-B == 0 , which is A == 0 as B is zero.
JMP ENDIF // jump to ENDIF point if A not equal to 0, else this step is skipped.
OUT // some statement , not called if A != 0.
ENDIF LDA A // jump statement arrives here if A != 0.
HLT //HALT
2) LMC Program:
//input first number
INP
//store it at address 99
STA 99
//input second number
INP
//add it to value at 99
ADD 99
//store the resulting sum to 99
STA 99
//input third number
INP
//add the number to value at 99 address(which is the sum of first and second number)
ADD 99
//output sum
OUT
//halt
HLT
Answer:
Option (B) i.e., Risk assessment is the correct answer to the following question.
Explanation:
The following option is correct because Risk assessment is the way you identify the risk and the hazardous factors related to risk and we can also say that it is the process of examining the tasks, process or that jobs which you are done to identify the objective of the risk.
So, that's why the Risk assessment is the correct option.
Answer:
I'm not sure if you can pick inbetween, but that's what I'm doing.
I believe that technology is both good and bad for society. Before technology and social media, things were much simpler. there was no cyber bullying, there were no eye problems due to phone and computer screens, insomnia was less common, and people spent more personal time together. But, with access to technology, you can easily contact family members or 9-1-1 in case of emergencies, you can stay up to date on news, you can keep yourself entertained for extended amounts of time, you can talk to new people every day, and you can find information in seconds.
so, in conclusion, there are good and bad things about technology.
Explanation:
I dont have Instagram....
Answer:
B. Process, group of techniques
Explanation:
Data warehousing simply means storing large amounts of data from multiple sources to a central "warehouse" to be analyzed or simply stored for later. Data mining on the other hand involves discovering patterns in sets of data to make better decisions. Analyzing data with a group of techniques like statistics and machine learning.