MANAGEMENT INFORMATION SYSTEMS LOOSELEAF
16th Edition
ISBN: 9780135205518
Author: LAUDON
Publisher: PEARSON
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Chapter 4.4, Problem 2.3CQ
Explanation of Solution
Solving the problem of smartphones reducing cognitive skills:
- The smartphone technology these days have a large influence on a person’s attention, thinking and behavior. Even though its functions have become very useful, as observed by Nicholas Carr, this impact of smartphone has weakened an individual’s intellect, thereby growing his dependency on the technology.
- Carr highlights on the work done by cognitive psychologist Adrian Ward. Smartphones divide attention of an individual thereby impeding his reasoning and performance. Ward, Professor at University of Texas has observed that smartphone usage produces distractions which makes it harder to concentrate on a difficult problem...
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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 4 Solutions
MANAGEMENT INFORMATION SYSTEMS LOOSELEAF
Ch. 4.4 - Prob. 1.1CQCh. 4.4 - Prob. 1.2CQCh. 4.4 - Prob. 2.1CQCh. 4.4 - Prob. 2.2CQCh. 4.4 - Prob. 2.3CQCh. 4 - Prob. 1IQCh. 4 - Prob. 2IQCh. 4 - Prob. 3IQCh. 4 - Prob. 4IQCh. 4 - Prob. 5IQ
Ch. 4 - Prob. 1RQCh. 4 - Prob. 2RQCh. 4 - Prob. 3RQCh. 4 - Prob. 4RQCh. 4 - Prob. 5DQCh. 4 - Prob. 6DQCh. 4 - Prob. 7DQCh. 4 - Prob. 8HMPCh. 4 - Prob. 9HMPCh. 4 - Prob. 11HMPCh. 4 - Prob. 12CTPCh. 4 - Prob. 13CSQCh. 4 - Prob. 14CSQCh. 4 - Prob. 15CSQCh. 4 - Prob. 16CSQCh. 4 - Prob. 17MLMCh. 4 - Prob. 18MLM
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