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1. Apply the variant Breadth-First Search algorithm as shown in Figure 2 to the attached graph. This variant is used for computing the shortest distance to each vertex from the starting vertex. (Use this for your programming exercise.)
2. For this exercise, start at Carroll County. Process the adjacent vertices in alphabetical order.
3. You can stop after you have answered both questions (you don't have to finish the algorithm).
_ What are the first five counties to be removed from the queue, and what is the distance of each?
_ What counties are on the queue after the fifth county is removed, and what are their distance numbers? (You can stop after the county is removed and before its edges have been added to the queue.)
SPARSE MATRICES Matrices along with good number of zero entries are called sparse matrices. Refer the following matrices of Figure (a)
what algorithms can i use for the above title in my project desing and implmentation of road transport booking system
Q. Prove the hypothesis that "A tree having 'm' nodes has exactly (m-1) branches". Ans: A tree having m number of nodes has exactly (m-1) branches Proof: A root
Write an algorithm for binary search. Algorithm for Binary Search 1. if (low> high) 2. return (-1) 3. Mid = (low + high)/2 4. if ( X = = a[mid]) 5. return (mid); 6.
Question 1. How can you find out the end of a String? Write an algorithm to find out the substring of a string. 2. Explain the insertion and deletion operation of linked lis
Define what an algorithm is and outline the characteristics of a good algorithm.
Define the Internal Path Length The Internal Path Length I of an extended binary tree is explained as the sum of the lengths of the paths taken over all internal nodes- from th
Simplifying Assumptions of wire frame representation Neglect colour - consider Intensity: For now we shall forget about colour and restrict our discussion just to the intensi
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Depth-first traversal A depth-first traversal of a tree visit a node and then recursively visits the subtrees of that node. Likewise, depth-first traversal of a graph visits
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