Database Design: The second stage of DBLC (Database Life cycle) is the database design. DBLC is a sequential process which is used to trace the history of the application that is present within the information system . The design phase consists of three stages and they are: Conceptual design Design a database that is independent of software and physical details. Logical design The main design goal is to make an enterprise wide database. Design a database that is based on the specific data model but independent of physical details. Physical design It is used to determine the storage capabilities of the data in an organization and its access characteristics. It ensures the integrity, security and performance.

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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 9, Problem 13RQ

Program Plan Intro

Database Design:

The second stage of DBLC (Database Life cycle) is the database design.

DBLC is a sequential process which is used to trace the history of the application that is present within the information system.

The design phase consists of three stages and they are:

Conceptual design

Design a database that is independent of software and physical details.

Logical design

The main design goal is to make an enterprise wide database.

Design a database that is based on the specific data model but independent of physical details.

Physical design

It is used to determine the storage capabilities of the data in an organization and its access characteristics.

It ensures the integrity, security and performance.

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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?