NIST: NIST refers “The National Security Telecommunications and Information system Security Committee” document. This document offerings a complete model for information security . It mentions the documentation of performance measurements in a regular format to guarantee the repeatability of the measurement collection, development, customization, and reporting activities. Contingency planning: A contingency planning is a course of action planned to support an organization respond efficiently to a significant future situation that may or may not happen. It is referred as “plan B” because it can be used as an alternative for action if estimated outputs fail to occur.

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Could you fix this? My marker has commented, What's missing? The input list is the link below. https://gmierzwinski.github.io/bishops/cs321/resources/CS321_Assignment_1_Input.txt result.put(true, dishwasherSum); result.put(false, sinkSum); return result; }}

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Chapter 10, Problem 4RQ

Program Plan Intro

NIST:

NIST refers “The National Security Telecommunications and Information system Security Committee” document. This document offerings a complete model for information security.

It mentions the documentation of performance measurements in a regular format to guarantee the repeatability of the measurement collection, development, customization, and reporting activities.

Contingency planning:

A contingency planning is a course of action planned to support an organization respond efficiently to a significant future situation that may or may not happen.

It is referred as “plan B” because it can be used as an alternative for action if estimated outputs fail to occur.

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Could you fix this? My marker has commented, What's missing? The input list is the link below. https://gmierzwinski.github.io/bishops/cs321/resources/CS321_Assignment_1_Input.txt result.put(true, dishwasherSum); result.put(false, sinkSum); return result; }}

PLEG136: Week 5 Portofolio Project Motion to Compel

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?