EBK BUSINESS DRIVEN TECHNOLOGY
7th Edition
ISBN: 8220103675451
Author: BALTZAN
Publisher: YUZU
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Question
Chapter 12, Problem 1OC
Program Plan Intro
Enterprise resource planning:
- It is nothing but a planning that joins various departments and its functions all over an organization into a single
information system . - This planning helps the employees to make their decisions on viewing the wide enterprise information about various business operations.
- The main motive is to provide common
database that supports various functions used by different business departments.
Example:
Consider the departments named sales and accounting that depend on the same data for their own needs.
Expert Solution & Answer
Explanation of Solution
Measuring the success of a connected car similar to measuring the success of ERP system:
- Connected car run from the producer to the customer while the ERP runs end to end all through the organization.
- If the garage door is open and a stray raccoon begins pulling the parts off a car is not the fault of the car. The connections in the system couldn’t monitor all the areas like that it is hard for an ERP system to monitors the complete business.
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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 12 Solutions
EBK BUSINESS DRIVEN TECHNOLOGY
Ch. 12 - Prob. 1OCCh. 12 - Prob. 2OCCh. 12 - Prob. 3OCCh. 12 - Prob. 1CQCh. 12 - Prob. 2CQCh. 12 - Prob. 3CQCh. 12 - Prob. 4CQCh. 12 - Prob. 1RQCh. 12 - Prob. 2RQCh. 12 - Prob. 3RQ
Ch. 12 - Prob. 4RQCh. 12 - Prob. 5RQCh. 12 - Prob. 6RQCh. 12 - Prob. 7RQCh. 12 - Prob. 1MBDCh. 12 - Prob. 2MBDCh. 12 - Prob. 3MBDCh. 12 - Prob. 4MBDCh. 12 - Prob. 5MBDCh. 12 - Prob. 1CCOCh. 12 - Prob. 2CCOCh. 12 - Prob. 3CCOCh. 12 - Prob. 4CCOCh. 12 - Prob. 5CCOCh. 12 - Prob. 1CCTCh. 12 - Prob. 2CCTCh. 12 - Prob. 3CCTCh. 12 - Prob. 4CCTCh. 12 - Prob. 5CCTCh. 12 - Prob. 6CCTCh. 12 - Prob. 1AYKCh. 12 - Prob. 2AYKCh. 12 - Prob. 3AYKCh. 12 - Prob. 5AYKCh. 12 - Prob. 6AYKCh. 12 - Prob. 7AYK
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