EBK BUSINESS DRIVEN TECHNOLOGY
EBK BUSINESS DRIVEN TECHNOLOGY
7th Edition
ISBN: 8220103675451
Author: BALTZAN
Publisher: YUZU
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Chapter 13, Problem 10RQ
Program Plan Intro

E-business:

The information and communication technology that is used for business activities is called as eBusiness.

  • eBusiness uses the internet to buy, sell, provide customer service and collaborate with business partners.
  • The eBusiness plays in the global market by providing the best customer service, giving materials economically and develops the products more efficiently.

ECommerce:

The process of eCommerce is to buy and sell the goods and services via electronic channels over the internet.

  • eCommerce is also called as electronic commerce.
  • A computer application eCommerce refers to the buying and selling of goods and services via electronic channels over the internet.
  • Even though the technologies available such as e-mail, social media, and mobiles, the modern eCommerce mostly uses the internet for the online purchasing of products.
  • It is the most efficient method to communicate within the organization of business transactions such as maintaining the financial records of the users such as bank balances, name, and address. But it is just a part of eCommerce business.
  • Use of eCommerce:
    • ECommerce is used to collect the demographic data through the web.
    • It provides the security over the business transactions.

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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)
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