EBK BUSINESS DRIVEN TECHNOLOGY
7th Edition
ISBN: 8220103675451
Author: BALTZAN
Publisher: YUZU
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Chapter 5, Problem 4AYK
Explanation of Solution
Measuring Efficiency and Effectiveness:
Plan to measure efficiency and effectiveness:
A plan to measure the effectiveness and efficiency of a course is as follows.
- In order to understand the needs, mission, capability and performance criteria of the students, work with the users.
- For evaluating the effectiveness of the
program , take out alternative source of action and plans. - Encourage and motivate the participation of the students.
- Identify the commendable changes that should be made if any...
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Students have asked these similar questions
Design a dynamic programming algorithm for the Longest Alternating Subsequence problem
described below:
Input: A sequence of n integers
Output: The length of the longest subsequence where the numbers alternate between being larger and
smaller than their predecessor
The algorithm must take O(n²) time. You must also write and explain the recurrence.
Example 1:
Input: [3, 5, 4, 1, 3, 6, 5, 7, 3, 4]
Output: 8 ([3, 5, 4, 6, 5, 7, 3, 4])
Example 2:
Input: [4,7,2,5,8, 3, 8, 0, 4, 7, 8]
Output: 8 ([4, 7, 2, 5, 3, 8, 0,4])
(Take your time with this for the subproblem for this one)
Design a dynamic programming algorithm for the Coin-change problem described below:
Input: An amount of money C and a set of n possible coin values with an unlimited supply of each
kind of coin.
Output: The smallest number of coins that add up to C exactly, or output that no such set exists.
The algorithm must take O(n C) time. You must also write and explain the recurrence.
Example 1:
Input: C24, Coin values = = [1, 5, 10, 25, 50]
Output: 6 (since 24 = 10+ 10+1+1 +1 + 1)
Example 2:
Input: C = 86, Coin values = [1, 5, 6, 23, 35, 46, 50]
Output: 2 (since 86 = 46+35+5)
Design a dynamic programming algorithm for the Longest Common Subsequence problem de-
scribed below
Input: Two strings x = x1x2 xm and y = Y1Y2... Yn
Output: The length of the longest subsequence that is common to both x and y.
.
The algorithm must take O(m n) time. You must also write and explain the recurrence.
(I want the largest k such that there are 1 ≤ i₁ < ... < ik ≤ m and 1 ≤ j₁ < ... < jk ≤ n such that
Xi₁ Xi2 Xik = Yj1Yj2 ··· Yjk)
Example 1:
Input: x = 'abcdefghijklmnopqrst' and y = 'ygrhnodsh ftw'
Output: 6 ('ghnost' is the longest common subsequence to both strings)
Example 2:
Input: x = 'ahshku' and y = ‘asu'
Output: 3 ('asu' is the longest common subsequence to both strings)
Chapter 5 Solutions
EBK BUSINESS DRIVEN TECHNOLOGY
Ch. 5 - Prob. 1OCCh. 5 - Prob. 2OCCh. 5 - Prob. 1CQCh. 5 - Prob. 2CQCh. 5 - Prob. 3CQCh. 5 - Prob. 4CQCh. 5 - Prob. 1RQCh. 5 - Prob. 2RQCh. 5 - Prob. 3RQCh. 5 - Prob. 4RQ
Ch. 5 - Prob. 5RQCh. 5 - Prob. 6RQCh. 5 - Prob. 7RQCh. 5 - Prob. 8RQCh. 5 - Prob. 1MBDCh. 5 - Prob. 2MBDCh. 5 - Prob. 3MBDCh. 5 - Prob. 4MBDCh. 5 - Prob. 1CCOCh. 5 - Prob. 2CCOCh. 5 - Prob. 3CCOCh. 5 - Prob. 5CCOCh. 5 - Prob. 1CCTCh. 5 - Prob. 2CCTCh. 5 - Prob. 3CCTCh. 5 - Prob. 4CCTCh. 5 - Prob. 5CCTCh. 5 - Prob. 1AYKCh. 5 - Prob. 2AYKCh. 5 - Prob. 3AYKCh. 5 - Prob. 4AYKCh. 5 - Prob. 6AYKCh. 5 - Prob. 10AYK
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