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【Scalable Cross-Platform】Scalable Cross-Platform Software Design:
Coursework#3 – Assessment on JAVA and GUI Topic
25% of the module mark.
Read the marking scheme on Moodle to familiarised with what I am looking for.
Coursework Instructions:

  1. Please submit as a single zip file which contains the whole NetBeans project folder
    and a brief report (max 10 pages).
  2. The NetBeans project should be prepared using JDK v8 and JavaFX v8 and should run
    in my PC without modification. (how to install documents are in Moodle)
  3. Graphical User Interface (GUI) will based on JavaFX v8 platform
  4. The report will describe the answer for each Questions, (i.e. class name and their
    purpose) and evidence to convince the client that it works correctly.
    Document date: 20/09/2020
    Context description
    A well-known Aerospace company AirCoach requests you to design and implement
    software with a user-friendly user interface to be integrated with their optical roughness
    metrology device. Their plan is to use the optical roughness device to measure “how
    smooth” the inner-lining of the inner engine cylinder of their new flagship plane Nimbus
  5. As they found from simulation that roughness of the engine cylinder degrades the
    engine’s efficiency, lifetime, and increases carbon and noise emission.
    Figure 1 Illustration of the cylinder and the roughness on the surface of an engine cylinder.
    2
    You have been supplied with the manual of the optical roughness metrology device
    which describes with the working principle of the device. You note that the most
    important aspect which related to your task, to develop the accompanying software, is
    that the device will output a text file which lists the roughness as the deviation in the
    unit of meter from an ideal circle (see Fig. 1).
    For illustration purposes, the first few lines of such text file are given in Fig. 2,
    6.000199e-05
    -4.671694e-05
    -1.083731e-04
    -1.894823e-04
    1.119588e-04
    …
    Figure 2 Few lines of the content of the measurement device in the unit of meter.
    Specifically, the engine designers need the following information from the measurements
    and wish that your software can provide it,
  6. Has a user-friendly user interface
  7. Streaming from the text file, to have the text file as an input
  8. Calculate the mean, variance, median and standard deviation of
  9. Plot the normalised histogram of the deviation , with an option to choose
    different bin method.
  10. Fit and plot the histogram with a Probability Density Function model (PDF).
  11. Save the histogram and the fitted PDF as a Bitmap png file.
  12. The software should also display the fitting parameters. For example: , and
    for Normal Probability Density Function (Advice 3).
    This is the context of the coursework.
    You will work on this coursework through a step-by-step following the Questions given
    in the following. Going through the Questions in-sequence will help you through
    finishing the coursework.
    Mark will be given for each Questions and its corresponding Tasks.
    3
    Question 1: [Mark 10%]
    Develop a JAVA package called binmethod which contains the implementation of
    Square root choice, Sturge’s and Rice rule bin rule formulae (see Review on the
    mathematics 1 box). The package will comprise of three concrete classes (i.e. the three
    bin rule formulae) and an Abstract Parent class called BinFormulae.
    The client code Unit_test_binmethod.java will drive your code to compute the
    number of bins for different bin rule formulae.
    Unit_test_binmethod.java
    /*
    Client code to test the binmethod package
    */
    import java.util.List;
    import java.util.Arrays;
    // the bin rule formulae must be implemented in binmethod package
    import binmethod.*;
    public class Unit_test_binmethod
    {
    public static void main(String[] args) {
    // Create array of data
    List exampleData = https://www.it610.com/article/Arrays.asList(1., 2., 3., 4., 5., 6., 7., 8., 9., 10.,11.);
    // test SturgesFormula class
    SturgesFormula SturgesInstance = new SturgesFormula(exampleData);
    SturgesInstance.calculateNumberOfBins();
    System.out.printf("By Sturges Formula: %d \n", SturgesInstance.getNumberOfBins());
    // test SquareRootChoice class
    SquareRootChoice SquareRootChoiceInstance = new SquareRootChoice(exampleData);
    SquareRootChoiceInstance.calculateNumberOfBins();
    System.out.printf("By Square Root Formula: %d \n", SquareRootChoiceInstance.getNumberOfBins());
    // test RiceRule class
    RiceRule RiceRuleInstance = new RiceRule(exampleData);
    RiceRuleInstance.calculateNumberOfBins();
    System.out.printf("By Rice Rule Formula: %d \n", RiceRuleInstance.getNumberOfBins());
    }
    }
    Task 1a: Draw and discuss an UML diagram which show the member and the relations
    between classes in the binmethod package.
    Task 1b: Implement the classes so that the Unit_test_binmethod.java client
    code will drive your code.
    Review on the mathematics 1
    In statistics, histogram is used to present the distribution of certain distributed data
    into several clusters. For example, the distribution of income in the country or the
    number of CoV-19 cases.
    4
    The first step in drawing a histogram is to “bin” the data into several cluster of value
    marker, i.e. salary range or time in the examples given above.
    There are several ways to determine the “number of bin” and there is no best way to
    decide the “bin-width” or the “number of bin” as different “bin-width” or the “number
    of bin” may reveal different features of data. In general, a good bin should
    ? Bins should be all the same size. See below how to calculate the bin size.
    ? Bins should include all the data.
    It is common to display histogram using different bin number which can be calculated
    using:
    ? Square root choice formula
    = √
    ? Sturge’s formula
    = 3.3 log + 1
    ? Rice rule formula
    = 2√
    3
    where, is the number of bins, is the total number of observation/measurement
    data and log() is natural logarithm operator.
    Question 2: [Mark 30%]
    Task 2a: Develop a package named statutils which has the capability to calculate
    basic statistical figures (i.e. mean, variance, max, min, median and standard deviation).
    Task 2b: Add a capability to count the number of data in each bin.
    5
    Task 2c: Add a capability to perform histogram normalisation (see Review on the
    mathematics 2 box).
    Task 2d: Write client class with a main function which perform the unit testing of the
    member functions, similar to the Unit_test_binmethod.java.
    Task 2e: Draw and discuss an UML diagram which show the member of the class,
    including their input and output arguments.
    You may make several classes to perform Task 2a – Task 2d and
    they should all in the statutils package.
    Review on the mathematics 2
    A histogram show “how many times” a certain value is observed from measurement,
    i.e. frequency of data. Thus, its magnitude changes depending on the total number of
    measurements. This type-of histogram is called un-normalised histogram.
    A normalised histogram, on the other hand, shows what is the probability of a certain
    value will be observed if there is an infinite number of measurements. Mathematically,
    this means that the area under the curve is equal to 1. In most cases, a normalised
    histogram is more useful than the un-normalised histogram in representing a large
    measurement data as is our task.
    Normalised frequency is obtained by dividing the number of observation in each bin by
    the unnormalized_data_count*bin_size, where the bin_width = (max(measurement
    data) - min(measurement data))/k and k is the “number of bins”.
    Question 3: [Mark 10%]
    Task 3a: Develop a package named mathutils in which contains a class to perform
    data fitting. The class will have static member functions to calculate the fitting
    parameters of the histogram (i.e. , , and parameters in the Review on the
    mathematics 3 box). The static function will use GaussianCurveFitter class
    implemented within the commons-math library from Apache.
    Review on the mathematics 3
    6
    You need a normalised histogram to fit with a Probability Density Function (PDF). In our
    case, Normal PDF is appropriate and is given by
    where the PDF parameters are,
    is the normalisation coefficient
    is the centre of the PDF
    is the width of the PDF.
    There are several ways to fit the histogram to a PDF, the most well-known method is
    called Levenberg-Marquardt method.
    Figure shows an example of an unnormalised histogram (left) and normalised with
    fitted Normal PDF (right).
    WE ARE NOT GOING INTO THE DETAIL OF MARQUARDT METHOD. IT IS QUITE MATHEMATICAL AND
    OUT OF THE SCOPE OF THE MODULE.
    I HAVE PROVIDED A NETBEANS PROJECT IN MOODLE IN WHICH I DEMONSTRATE THE USE OF WELLDEVELOPED
    OPEN-SOURCED LIBRARY FROM APACHE WHICH IMPLEMENT THE MARQUARDT
    METHOD. DOCUMENTATION OF THE LIBRARY CAN BE SEEN IN
    http://commons.apache.org/pro...
    Question 4: [Mark 35%]
    Task 4a: Develop and implement an operational Graphical User Interface application
    satisfying the client request:
  13. Has a user-friendly user interface
  14. Streaming from the text file, to have the text file as an input
    7
  15. Calculate and display the mean, variance, median and standard deviation of
    measurement data
  16. Plot the normalised histogram of the deviation , with an option to choose
    different bin method.
  17. Fit and plot the histogram with a Probability Density Function model (PDF).
  18. Save the histogram and the fitted PDF as a Bitmap png file.
  19. The software should also display the fitting parameters. For example: , and
    for Normal Probability Density Function (Advice 3).
    Task 4b: Draw the hierarchical order of the GUI nodes.
    Task 4c: Draw and discuss the GUI Event Handling UML diagrams of your app.
    Good Programming Practice - [Mark 15%]
    Detail on expected good programming practice is given in the rubric
    End of document.

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