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https://www.dropbox.com/s/nog0nuhgbjg35uy/SoundLibrary.zip?dl=0


Purpose


This assignment will sum up the Animatesection of the course. You will work independently to create unique artwork that meets specific technical standards.


Getting Started




  • Downloadthe file archives linked above. Read through the assignment instructions and explore the sample files and resources.


  • Brainstorm. Try to come up with an engaging idea for this project before you turn on the computer. Consider sketching or outlining potential ideas to help you zero-in on the one that seems the most engaging.



  • Step-by-step suggestionsfor planning and building this file are included in the assignment instructions!





Project Requirements




  • File specs:900 x 600 pixels. 5-10 second animation.

  • One pixel element created in Photoshop.

  • At least two vector elements from your final Illustrator project.

  • A layer containing type.

  • A layer containing sound.

  • No fewer than 4 separate tweens [motion, shape]



Delivery


You will turn in only the native FLA when you have completed this project




  • Wong_WingTung_ANFinal


animatefinalprojectstoryboard-icndjrcu.pdf animatefinalprojectsamples-xhhcszgm.zip animatefinalprojectinstructions-cxga5a2c.pdf
Answered 7 days After Nov 07, 2024

Solution

Pashikanti Sneha answered on Nov 15 2024
3 Votes
Question 1 -
To solve this problem, let's consider the two approaches and evaluate their time complexities.
Approach 1: Running Dijkstra’s Algorithm k Times
1. Algorithm: In this approach, we use Dijkstra's algorithm k times, once for each of the k starting vertices, to compute the shortest path from each to the goal.
2. Time Complexity: Running Dijkstra’s algorithm from a single source to a single goal takes O((n+m)log⁡n), where mmm is the number of edges in G. Since we are running it k times, the overall time complexity becomes: O(k⋅(n+m)log⁡n)
Approach 2: Modified Dijkstra’s Algorithm Starting from the Goal
1. Algorithm:
· We start by reversing the edges of the graph G to create a new graph G′.
· Then, we apply Dijkstra's algorithm from the goal vertex in G’.
· Since G′ has reversed edges, running Dijkstra’s algorithm from the goal vertex in G′ will effectively compute the shortest path from the goal to every other vertex in G, which includes the k vertices of interest.
2. Co
ectness: By reversing the edges and running Dijkstra’s algorithm from the goal in G′, we are effectively finding the shortest path from each of the k vertices to the goal in the original graph G. This modification is co
ect because Dijkstra’s algorithm, applied on G′ from the goal, computes shortest paths in a way that co
esponds to paths in G towards the goal.
3. Time Complexity: Running Dijkstra’s algorithm once on G′ from the goal vertex takes O((n+m)log⁡n), as we process all vertices and edges only once. This is more efficient than running the algorithm k times, so the complexity of this approach is:
O((n+m)log⁡n)
Summary
· First approach: O(k⋅(n+m)log⁡n)
· Second approach: O((n+m)log⁡n)
The second approach is more efficient when k is greater than 1, making it preferable for solving this problem.
Question 2 -
If we apply the algorithm for Topological Sorting on a graph G that is not a Directed Acyclic Graph (DAG), the following will occur:
1. Detection of a Cycle:
· Topological sorting is only valid for DAGs. If G is not a DAG (i.e., it contains a cycle), the algorithm will encounter a problem.
· Specifically, when attempting to process the vertices, it will fail to resolve...
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