Enterprise computing: A large organization called as an enterprise requires a computing solutions because of its size and geographic distribution. An enterprise contains many departments, centers and divisions, which are collectively called as functional units.

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B A E H Figure 1 K Questions 1. List the shortest paths between all node pairs. Indicate the number of shortest paths that pass through each edge. Explain how this information helps determine edge betweenness. 2. Compute the edge betweenness for each configuration of DFS. 3. Remove the edge(s) with the highest betweenness and redraw the graph. Recompute the edge betweenness centrality for the new graph. Explain how the network structure changes after removing the edge. 4. Iteratively remove edges until at least two communities form. Provide step-by-step calculations for each removal. Explain how edge betweenness changes dynamically during the process. 5. How many communities do you detect in the final step? Compare the detected communities with the original graph structure. Discuss whether the Girvan- Newman algorithm successfully captures meaningful subgroups. 6. If you were to use degree centrality instead of edge betweenness for community detection, how would the results change?

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Chapter 4, Problem 24SG

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Enterprise computing:

A large organization called as an enterprise requires a computing solutions because of its size and geographic distribution. An enterprise contains many departments, centers and divisions, which are collectively called as functional units.

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B A E H Figure 1 K Questions 1. List the shortest paths between all node pairs. Indicate the number of shortest paths that pass through each edge. Explain how this information helps determine edge betweenness. 2. Compute the edge betweenness for each configuration of DFS. 3. Remove the edge(s) with the highest betweenness and redraw the graph. Recompute the edge betweenness centrality for the new graph. Explain how the network structure changes after removing the edge. 4. Iteratively remove edges until at least two communities form. Provide step-by-step calculations for each removal. Explain how edge betweenness changes dynamically during the process. 5. How many communities do you detect in the final step? Compare the detected communities with the original graph structure. Discuss whether the Girvan- Newman algorithm successfully captures meaningful subgroups. 6. If you were to use degree centrality instead of edge betweenness for community detection, how would the results change?

Unit 1 Assignment 1 – Loops and Methods (25 points) Task: You are working for Kean University and given the task of building an Email Registration System. Your objective is to generate a Kean email ID and temporary password for every new user. The system will prompt for user information and generate corresponding credentials. You will develop a complete Java program that consists of the following modules: Instructions: 1. Main Method: ○ The main method should include a loop (of your choice) that asks for input from five users. For each user, you will prompt for their first name and last name and generate the email and password by calling two separate methods. Example о Enter your first name: Joe Enter your last name: Rowling 2.generateEmail() Method: This method will take the user's first and last name as parameters and return the corresponding Kean University email address. The format of the email is: • First letter of the first name (lowercase) + Full last name (lowercase) +…

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