Management Information Systems: Managing The Digital Firm -- Student Value Edition (16th Edition)
16th Edition
ISBN: 9780135191927
Author: Kenneth Laudon, Jane Laudon
Publisher: PEARSON
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Expert Solution & Answer
Chapter 3.3, Problem 2.2CQ
Explanation of Solution
Smart products changing the operations and decision making for organization:
- A digital coaching feature is recently added by Under Armour which is used to run the connected shoes and Map My Run application.
- Runners will have an ability to monitor their gait and stride length mile after mile, and also see how that impacts their pace and cadence...
Explanation of Solution
Smart products changing the behavior of users:
- Under Armour is believing that daily use of smartphone apps will build stronger relationship with customers this leads to stronger sales.
- The company benefiting from bringing the power of software to its physical products.
- The smart meter will let the company know when a customer loses service which resulting in faster repairs.
- This provide real-time billing information to customers based on energy usage, enabling them to pinpoint areas for energy savings...
Expert Solution & Answer
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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 3 Solutions
Management Information Systems: Managing The Digital Firm -- Student Value Edition (16th Edition)
Ch. 3.3 - Prob. 1.1CQCh. 3.3 - Prob. 1.2CQCh. 3.3 - Prob. 1.3CQCh. 3.3 - Prob. 1.4CQCh. 3.3 - Prob. 2.1CQCh. 3.3 - Prob. 2.2CQCh. 3.3 - Prob. 2.3CQCh. 3 - Prob. 1IQCh. 3 - Prob. 2IQCh. 3 - Prob. 3IQ
Ch. 3 - Prob. 4IQCh. 3 - Prob. 1RQCh. 3 - Prob. 2RQCh. 3 - Prob. 3RQCh. 3 - Prob. 4RQCh. 3 - Prob. 5DQCh. 3 - Prob. 6DQCh. 3 - Prob. 7DQCh. 3 - Prob. 8HMPCh. 3 - Prob. 9HMPCh. 3 - Prob. 11HMPCh. 3 - Prob. 12CTPCh. 3 - Prob. 13CSQCh. 3 - Prob. 14CSQCh. 3 - Prob. 15CSQCh. 3 - Prob. 16CSQCh. 3 - Prob. 17MLMCh. 3 - Prob. 18MLM
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