The user interface (correct answer is a)
Answer:
Here is the program for the given question
Explanation:
class StringSet
{
ArrayList<String> arraylist; //a reference variable of ArrayList of generic type String
//A no argument constructor.
public StringSet()
{
arraylist=new ArrayList<String>(); //instantiating the ArrayList object
}
//A mutator that adds a String newStr to the StringSet object.
void add(String newStr)
{
arraylist.add(newStr); // add(String) method to add string to the arraylist
}
//An accessor that returns the number of String objects that have been added to this StringSet object.
int size()
{
return arraylist.size(); // size() method which gives the number of elements in the list
}
//An accessor that returns the total number of characters in all of the Strings that have been added to this StringSet object.
int numChars()
{
int sum = 0;
for(String str:arraylist) //for-each loop; can be read as for each string in arraylist
{
sum+=str.length();
}
return sum;
}
//An accessor that returns the number of Strings in the StringSet object that have exactly len characters.
int countStrings(int len)
{
int count = 0;
for(String str:arraylist)
{
if(str.length() == len)
count++;
}
return count;
}
}
Answer:
Your answer will be output.
Hope this helps!
Answer:
Algorithmic bias.
Explanation:
An algorithm can be defined as a standard formula or procedures which comprises of set of finite steps or instructions for solving a problem on a computer. The time complexity is a measure of the amount of time required by an algorithm to run till its completion of the task with respect to the length of the input.
An algorithmic bias can be defined as a systematic error or prejudice in a computer algorithm which typically generate outcomes that are unfair or unfavorable and as such giving unparalleled privileges to a demography (users) over the rest users.
In this scenario, a healthcare start-up is using Artificial Intelligence (AI) to test the way a person speaks in order to detect Alzheimer's disease. The algorithm interprets pauses and differences in pronunciations as markers of the disease. The developers used a dataset that contains only speech samples from native English speakers. Thus, the type of bias that is present in this example is an algorithmic bias.
