5-1 Discussion Behavior Model
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5-1 Discussion: Behavior Model: Maintain Class Records Sequence Diagram
Despite making a few corrections, I am still uncertain about the accuracy of my completion.
To begin creating the sequence diagram, I first had to determine its appearance and construction. It took
me some time to figure out the diagram layout, especially with the pre-built UML components in Visio.
Then, I examined the events to establish the sequence, starting with the staff. As I progressed through
the events, I realized that the staff would need to perform additional tasks based on the student's
selection. For example, when a student registers for a class, the staff must either enroll them in an
existing class or create a new one (online or in-person) for them to enroll in. If the class is online, the
staff must provide the URL and browser, and if it's in-person, they must provide the building and
classroom information. These actions are recorded in the class database by the staff.
At first, I found myself slightly perplexed by the assignment's instructions regarding the intended use of
the form to be submitted. However, once I comprehended that the provided information was meant to
facilitate the creation of the diagram rather than the card and diagram itself, a moment of enlightenment
ensued. The sequence diagram struck a chord with me as I drew a loose analogy between it and a flow
chart process. While this perspective may not universally apply, it proved effective for me. Furthermore,
the Courses & Classes Records Class Diagram proved invaluable in clarifying the required information.
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Related Questions
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https://www.youtube.com/watch?v=sUqKUbmdOr0
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Scenario
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Q: is the last two digits of your student Id number. If your number is (20110092) then Q=92.
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Task 1
Determine the gradient of following functions at the given points:
a) x(t) = (2t7 + P t-2)² + (6vi – 5) when t = 1
5s+7
b) v(s) =
when s = 3
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% Sample data for Diesel and Petrol cars
carPosition = linspace(1, 60, 50); % Assumed positions of cars
% Fix the random seed for reproducibility
rng(45);
% Assumed positions of cars
CO2Diesel = 25 + 5*cos(carPosition/60*2*pi) + randn(1, 50)*5; % Random data for Diesel
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fitPetrol = polyval(pPetrol, carPosition);
% Plotting the data
figure; hold on;
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carPosition = linspace(1, 60, 50); % Assumed positions of cars
% Define your seed here
seed = 50;
rand('seed',seed); % Set the seed for reproducibility
% Assumed CO2 emissions for Diesel and Petrol
CO2Diesel = 25 + 5*cos(carPosition/60*2*pi) + randn(1, 50)*5; % Random data for Diesel
CO2Petrol = 20 + 5*sin(carPosition/60*2*pi) + randn(1, 50)*5; % Random data for Petrol
% Fit polynomial curves with a reduced degree of 2
pDiesel = polyfit(carPosition, CO2Diesel, 2);
pPetrol = polyfit(carPosition, CO2Petrol, 2);
% Generate points for best fit lines
fitDiesel = polyval(pDiesel, carPosition);
fitPetrol = polyval(pPetrol, carPosition);
% Plotting the data
figure;
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% Plot Diesel best fit line…
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Please use this code and fix it in MATLAB:
% Sample data for Diesel and Petrol cars
carPosition = linspace(1, 60, 50); % Assumed positions of cars
% Fix the random seed for reproducibility
rng(50);
% Assumed positions of cars
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fitPetrol = polyval(pPetrol, carPosition);
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Use this code on MATLAB and fix it.
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carPosition = linspace(1, 60, 50); % Assumed positions of cars
% Fix the random seed for reproducibility
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% Sample data for Diesel and Petrol cars
carPosition = linspace(1, 60, 50); % Assumed positions of cars
% Use the 'seed' function instead of 'rng'
seed = 50; % Define your seed here
rand('seed',seed);
% Assumed CO2 emissions for Diesel and Petrol
CO2Diesel = 25 + 5*cos(carPosition/60*2*pi) + randn(1, 50)*5; % Random data for Diesel
CO2Petrol = 20 + 5*sin(carPosition/60*2*pi) + randn(1, 50)*5; % Random data for Petrol
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pDiesel = polyfit(carPosition, CO2Diesel, 2);
pPetrol = polyfit(carPosition, CO2Petrol, 2);
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Please use this code on MATLAB and fix it.
% Sample data for Diesel and Petrol cars
carPosition = linspace(1, 60, 50); % Assumed positions of cars
% Fix the random seed for reproducibility
rng(50);
% Assumed CO2 emissions for Diesel and Petrol
CO2Diesel = 25 + 5*cos(carPosition/60*2*pi) + randn(1, 50)*5; % Random data for Diesel
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fname = '00095337.fit';
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img = fitsread(fname);
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Use this code on MATLAB and add the purple line.
% Sample data for Diesel and Petrol cars
carPosition = linspace(1, 60, 50); % Assumed positions of cars
% Use the 'seed' function instead of 'rng'
seed = 50; % Define your seed here
rand('seed',seed);
% Assumed CO2 emissions for Diesel and Petrol
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CO2Petrol = 20 + 5*sin(carPosition/60*2*pi) + randn(1, 50)*5; % Random data for Petrol
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pDiesel = polyfit(carPosition, CO2Diesel, 2);
pPetrol = polyfit(carPosition, CO2Petrol, 2);
% Generate points for best fit lines
fitDiesel = polyval(pDiesel, carPosition);…
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OFocus
4:20 AM
28°C Mostly clear
3/26/2022
LG
CVENUENS
THANOS
BOBBLEHEAD
AMANLANTE A ON CABIA ANn
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YOP! AVENGES
KEYCHAIN
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-The exam is open adopted textbook, open class notes (posted notes and solutions on the class' Canvas site only) and you may use
Matlab's build-in help system, but only to look up Matlab syntax questions;
- no collaboration is allowed; no help, including the tutoring center, may be sought to solve the problems;
- exam questions may only be asked to the instructor via private Ed Discussion posts or during the instructor's office hours;
- for non Matlab Grader problems, document all steps you took to solve the problem. This can be handwritten, but must be legible
for credit. If the problem states 'By hand', do not use any script/function to actually solve the problem, however, you may use a
non-programmable calculator or script/functions coded in this class to help in verifying the numerical results of individual steps;
- on Gradescope associate/select your answer pages with the corresponding problem numbers. Failure to do so may result in
no points given initially and will require a…
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