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Python Programming: An Introduction to Computer Science
3rd Edition
ISBN: 9781590282779
Author: John Zelle
Publisher: Franklin Beedle & Associates
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Chapter 11, Problem 10PE
Program Plan Intro
Implementation of sieve
Program plan:
- Define the “sieve_era()” function,
- Create empty list.
- Create “while” loop,
- Append the first element to the new list using “append()” method.
- Make a “try” statement for exception.
- Create “for” loop,
- Check whether the list element is divided by the first element.
- If it is “True” remove the element.
- Create “for” loop,
- If any exception occurs, handle the exception,
- Keep the new list.
- Return new list.
- Define the “main()” function,
- Get the input from the user.
- Create empty list.
- Create “for” loop,
- Fill the new list using “append()” method.
- Assign the list return from “sieve_era()” function.
- Remove the element “4” from the list.
- Print the list.
- Call the “main()” function.
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11. Go to the Webinars worksheet. DeShawn wants to determine the number of webinars the company can hold on Tuesdays and Thursdays to make the highest weekly profit without interfering with consultations, which are also scheduled for Tuesdays and Thursdays and use the same resources.
Use Solver to find this information as follows:
a. Use Total weekly profit as the objective cell in the Solver model, with the goal of determining the maximum value for that cell.
b. Use the number of Tuesday and Thursday sessions for the five programs as the changing variable cells.
c. Determine and enter the constraints based on the information provided in Table 3.
d. Use Simplex LP as the solving method to find a global optimal solution.
e. Save the Solver model below the Maximum weekly profit model label.
f. Solve the model, keeping the Solver solution.
Table 3: Solver Constraints
Constraint Cell or Range
Each webinar is scheduled at least once on Tuesday and once on Thursday B4:F5
Each Tuesday and…
Go to the Webinars DeShawn wants to determine the number of webinars the company can hold on Tuesdays and Thursdays to make the highest weekly profit without interfering with consultations, which are also scheduled for Tuesdays and Thursdays and use the same resources. Use Solver to find this information as follows:
Use Total weekly profit as the objective cell in the Solver model, with the goal of determining the maximum value for that cell.
Use the number of Tuesday and Thursday sessions for the five programs as the changing variable cells.
Determine and enter the constraints based on the information provided in Table 3.
Use Simplex LP as the solving method to find a global optimal solution.
Save the Solver model below the Maximum weekly profit model label.
Solve the model, keeping the Solver solution.
Table 3: Solver Constraints
Constraint
Cell or Range
Each webinar is scheduled at least once on Tuesday and once on Thursday
B4:F5
Each Tuesday and Thursday…
I want to ask someone who has experiences in writing physics based simulation software. For context I am building a game engine, and want to implement physics simulation. There are a few approaches that I managed to find, but would like to know what are other approaches to doing physics simulation entry points from scenes, would you be able to visually draw me a few approaches (like 3 approaces)?
When I say entry point to the actual physics simulation. An example of this is when the user presses the play button in the editor, it starts and initiates the physics system. Applying all of the global physics settings parameters that gets applied to that scene.
Here is the use-case, I am looking for. If you have two scenes, and select scene 1. You press the play button. The physics simulation starts. When that physics simulation starts, you are also having to update the physics through some physics dedicated delta time because physics needs to happen faster update frequency.
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Chapter 11 Solutions
Python Programming: An Introduction to Computer Science
Ch. 11 - Prob. 1TFCh. 11 - Prob. 2TFCh. 11 - Prob. 3TFCh. 11 - Prob. 4TFCh. 11 - Prob. 5TFCh. 11 - Prob. 6TFCh. 11 - Prob. 7TFCh. 11 - Prob. 8TFCh. 11 - Prob. 9TFCh. 11 - Prob. 1MC
Ch. 11 - Prob. 2MCCh. 11 - Prob. 3MCCh. 11 - Prob. 4MCCh. 11 - Prob. 5MCCh. 11 - Prob. 6MCCh. 11 - Prob. 7MCCh. 11 - Prob. 8MCCh. 11 - Prob. 9MCCh. 11 - Prob. 10MCCh. 11 - Prob. 1DCh. 11 - Prob. 2DCh. 11 - Prob. 1PECh. 11 - Prob. 2PECh. 11 - Prob. 3PECh. 11 - Prob. 5PECh. 11 - Prob. 6PECh. 11 - Prob. 7PECh. 11 - Prob. 8PECh. 11 - Prob. 9PECh. 11 - Prob. 10PECh. 11 - Prob. 11PECh. 11 - Prob. 12PECh. 11 - Prob. 15PECh. 11 - Prob. 16PECh. 11 - Prob. 18PECh. 11 - Prob. 19PE
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