Draw a conceptual schema for the specification of a database domain listed above. Use the
notation of UML simplified class diagrams explained to you during this subject. Note: you are not
allowed to use any artificial identifiers and any attributes that are not mentioned in the specification.
Use UMLet to draw the schema and paste images of your drawings into your Microsoft Word
document. Add your name, student number and the date to your diagram. There is NO NEED to
provide a detailed analysis of how a conceptual schema has been created. The final conceptual
schema expressed in the UML simplified notation classes is subject is sufficient.
(7 marks)
Add two (2) new object classes with at least three (3) attributes each and appropriate associations.
The choice of object classes, attributes and associations are up to you; however, these should
relate to the existing scenario.
Use UMLet to draw the changes to the schema and paste the second diagram into your Microsoft
Word document. Write a text description that explains the additional objects, attributes and
associations below the diagram.
Draw a conceptual schema for the specification of a database domain listed above. Use the
notation of UML simplified class diagrams explained to you during this subject. Note: you are not
allowed to use any artificial identifiers and any attributes that are not mentioned in the specification.
Use UMLet to draw the schema and paste images of your drawings into your Microsoft Word
document. Add your name, student number and the date to your diagram. There is NO NEED to
provide a detailed analysis of how a conceptual schema has been created. The final conceptual
schema expressed in the UML simplified notation classes is subject is sufficient.
(7 marks)
Add two (2) new object classes with at least three (3) attributes each and appropriate associations.
The choice of object classes, attributes and associations are up to you; however, these should
relate to the existing scenario.
Use UMLet to draw the changes to the schema and paste the second diagram into your Microsoft
Word document. Write a text description that explains the additional objects, attributes and
associations below the diagram.
The purpose of this tutorial project is to tidy and wrangle data with methods from the “tidyr” and “dplyr” libraries so that the data can be used by clients, in an easy-to-use form. This project will focus on the following tasks: • Removing missing data, out-of-bounds values and unexpected values • Transformation to calculate new variables • Concatenate information regarding replicate measurements • Sub-sampling and stratification to make balanced distributions • Re-scaling and other transformations • Saving data sets in easy to read formats • Where a particular package or library is mentioned you must only provide solution using that package or library. Other solutions (even if correct) won’t receive marks. Data Sugar factories measure sugar cane juice at the start of the factory process to determine factory settings and to determine the economic value of the supplied sugar cane. To enable real time factory optimisation, a real-time measurement technology called near infrared spectroscopy (NIRS) is used. NIRS analyses the light spectrum that the sugar cane absorbs – the absorbance spectrum is correlated to the chemical composition of the sugar cane. However, the NIRS instruments need to be calibrated to measure specific components of the sugar cane. To do this, traditional laboratory measurements are collected and used to train (calibrate) the NIRS instruments. The first step in training the NIRS instruments is to prepare laboratory measurements. Because laboratories use multiple assays (different measurement types), measurement information is typically stored in different files or databases. This information needs to be collated, cleaned and appropriately sub-sampled to make training datasets for NIRS instruments.
a) DarwinCom Pty Ltd is made up of a number of departments that manage none or more projects.
Each project is made up of none or more team members. Each team member belongs to one
department and zero to one project. One of the team members supervise the other team members
on the project.
b) A company has four departments. Each department has one manager. Each department employs
staff. Each staff may work for one or more departments. A staff may be supervised by another
staff at least.
c) A car insurance company whose customers own one or more cars each. Each car has associated
with it zero to many number of recorded accidents.
d) A university registrar has the following entities: Courses (including course number, title, credits,
syllabus, and prerequisites); Course offerings, (including course number, year, teaching period,
instructors, timings and classroom); Students (including student-id, name, and program); and
Instructors (including identification number, name, department, and title). The enrolment of
students in courses and grades awarded to students in each course they are enrolled for must be
appropriately modelled. An instructor could teach in only one course. Each course only runs in
one session
Draw a conceptual schema for the specification of a database domain listed above. Use the
notation of UML simplified class diagrams explained to you during this subject. Note: you are not
allowed to use any artificial identifiers and any attributes that are not mentioned in the specification.
Use UMLet to draw the schema and paste images of your drawings into your Microsoft Word
document. Add your name, student number and the date to your diagram. There is NO NEED to
provide a detailed analysis of how a conceptual schema has been created. The final conceptual
schema expressed in the UML simplified notation classes is subject is sufficient.
(7 marks)
Add two (2) new object classes with at least three (3) attributes each and appropriate associations.
The choice of object classes, attributes and associations are up to you; however, these should
relate to the existing scenario.
Use UMLet to draw the changes to the schema and paste the second diagram into your Microsoft
Word document. Write a text description that explains the additional objects, attributes and
associations below the diagram.
The purpose of this tutorial project is to tidy and wrangle data with methods from the “tidyr” and “dplyr” libraries so that the data can be used by clients, in an easy-to-use form. This project will focus on the following tasks: • Removing missing data, out-of-bounds values and unexpected values • Transformation to calculate new variables • Concatenate information regarding replicate measurements • Sub-sampling and stratification to make balanced distributions • Re-scaling and other transformations • Saving data sets in easy to read formats • Where a particular package or library is mentioned you must only provide solution using that package or library. Other solutions (even if correct) won’t receive marks. Data Sugar factories measure sugar cane juice at the start of the factory process to determine factory settings and to determine the economic value of the supplied sugar cane. To enable real time factory optimisation, a real-time measurement technology called near infrared spectroscopy (NIRS) is used. NIRS analyses the light spectrum that the sugar cane absorbs – the absorbance spectrum is correlated to the chemical composition of the sugar cane. However, the NIRS instruments need to be calibrated to measure specific components of the sugar cane. To do this, traditional laboratory measurements are collected and used to train (calibrate) the NIRS instruments. The first step in training the NIRS instruments is to prepare laboratory measurements. Because laboratories use multiple assays (different measurement types), measurement information is typically stored in different files or databases. This information needs to be collated, cleaned and appropriately sub-sampled to make training datasets for NIRS instruments.
Assignment Content
- Overview
Name: Capstone project
Type: Data Visualisation and Pre-processing report
Due: 11:59 pm Week 13
Weight: 40%
This assessment involves writing a report that summarises a data science related investigation that you have conducted on data that you have collected yourself. The investigation must involve the main topics covered in the subject, most noticeably data pre-processing (representation, wrangling, tidying) and exploratory data visualisation using R/RStudio.
It is a merger of techniques learned for previous assessments. However the pre-processing/exploratory steps to be carried out will not be provided, you have to make independent choices and decisions. We won’t mark you for coding and as such there is no expectation that you submit codes. If however, you think particular coding segments may contribute to your presentation (and argument) you could include that as supplementary and highlight - and refer to that- that in the main text.
You are required to find your own data set.. However, your dataset cannot be smaller than 1000 observations of 5 variables, except if the targeted data science problem to be addressed relates to spatial-temporal data, in which case less than 5 dimensions could be allowed.
The report should not exceed 10 pages. The main body text must notbe longer than 5 pages. The rest of the (5) pages should incorporate any supplementary files, including graphs or codes (codes won’t be marked unless clearly indicated in main text or linked to the analysis).
Download the Capstone Project assignment document for full details of this assessmentincluding the marking scheme.
Assessment submission
If you use Word or any other program, save your work as a pdf for submission.
Include the following in your submission:
- Your work in pdf format
- The task cover sheet
- Upload both files at the same time.
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- Capstone_Project_MA1580.pdf</bb-rich-text-editor></bb-assessment-question>