Answer:
Explanation:
The following is written in Java. It creates the function num_eights and uses recursion to check how many times the digit 8 appears in the number passed as an argument. A test case has been created in the main method and the output can be seen in the image below highlighted in red.
public static int num_eights(int pos){
if (pos == 0)
return 0;
if (pos % 10 == 8)
return 1 + num_eights(pos / 10);
else
return num_eights(pos / 10);
}
Global source and binary.
Support for mixed-script computing environments.
Improved cross-platform data interoperability through a common codeset.
Space-efficient encoding scheme for data storage.
Reduced time-to-market for localized products.
Expanded market access.
Experiments. ...
Surveys. ...
Questionnaires. ...
Interviews. ...
Case studies. ...
Participant and non-participant observation. ...
Observational trials. ...
Studies using the Delphi method.
What do you mean? I don't understand.
Answer: True
Explanation:
Subset sum problem and Knapsack problem can be solved using dynamic programming.
In case of Knapsack problem there is a set of weights associative with objects and a set of profits associated with each object and a total capacity of knapsack let say C. With the help of dynamic programming we try to include object's weight such that total profit is maximized without fragmenting any weight of objects and without exceeding the capacity of knapsack, it is also called as 0/1 knapsack problem.
Similar to knapsack problem, in subset sum problem there is set of items and a set of weights associated with the items and a capacity let say C, task is to choose the subset of items such that total sum of weights associated with items of subset is maximized without exceeding the total capacity.
On the basis of above statements we can say that subset sum problem is generalization of knapsack problem.