Answer:
Make use of hash tables
Explanation:
The appropriate thing to use for this should be a hash table.
A Hash Table can be described as a data structure which stores data in an associative manner. In a hash table, data is stored in an array format, where each data value has its own unique index value. Access of data becomes very fast if we know the index of the desired data. So we can perform Hashing on ISBN Number since its unique and based on the Hash Function w ecan store the Information record.
There is no requirement for printing the file in order - HashTables dont store the data in order of insertions, so no problems with that
It becomes a data structure in which insertion and search operations are very fast irrespective of the size of the data. So Querying books details can be fast and searching will take less time.
It can also be pointed out that it wont be too expensive for Hardware implemtation as HashTables stores data based on Hash Functions and memory consumption is also optimal which reduces memory wastages.
Answer:
O(n^2)
Explanation:
The number of elements in the array X is proportional to the algorithm E runs time:
For one element (i=1) -> O(1)
For two elements (i=2) -> O(2)
.
.
.
For n elements (i=n) -> O(n)
If the array has n elements the algorithm D will call the algorithm E n times, so we have a maximum time of n times n, therefore the worst-case running time of D is O(n^2)
Answer:
Python file with appropriate comments given below
Explanation:
#Take the input file name
filename=input('Enter the input file name: ')
#Open the input file
inputFile = open(filename,"r+")
#Define the dictionary.
list={}
#Read and split the file using for loop
for word in inputFile.read().split():
#Check the word to be or not in file.
if word not in list:
list[word] = 1
#increment by 1
else:
list[word] += 1
#Close the file.
inputFile.close();
#print a line
print();
#The word are sorted as per their ASCII value.
fori in sorted(list):
#print the unique words and their
#frequencies in alphabetical order.
print("{0} {1} ".format(i, list[i]));
Answer:
Big Oh notation is used to asymptotically bound the growth of running time above and below the constant factor.
Big Oh notation is used to describe time complexity, execution time of an algorithm.
Big Oh describes the worst case to describe time complexity.
For the equation; T(N) = 10000*N + 0.00001*N^3.
To calculate first of all discard all th constants.
And therefore; worst case is the O(N^3).
Answer:
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
Where 
t and 
t
Substitute these values in the given formula
<em>(Approximated)</em>
