Note: This unit version is currently being edited and is subject to change!
CHNG5603: Analysis, Modelling, Control: BioPhy Sys (2017 - Semester 1)
|Unit:||CHNG5603: Analysis, Modelling, Control: BioPhy Sys (6 CP)|
|Faculty/School:||School of Chemical and Biomolecular Engineering|
A/Prof Dehghani, Fariba
|Session options:||Semester 1|
|Versions for this Unit:|
|Brief Handbook Description:||This course will give students an insight into the use of (computer-based) statistical techniques in extracting information from experimental data obtained from real life bio-physical systems. The issues and techniques required for mathematical modeling as well as monitoring and/or control scheme for bio-physical systems will be discussed and implemented in diverse range of bioprocesses, including biomaterials and fermentation products.
We will review statistical distribution; tests based on z, t, F variables; calculation of confidence intervals; hypothesis testing; linear and nonlinear regression; analysis of variance; principal component analysis; and use of computer-based statistical tools. The issues associated with dynamic response of bio-physical processes; inferred or estimated variables; control system design and implementation; introduction to model-based control; use of computer-based control system design and analysis tools will be elaborated.
When this course is successfully completed you will acquire knowledge to choose the appropriate statistical techniques within a computer based environment, such as Excel or MATLAB, for a given situation. The students will also obtain potential for monitoring/control scheme based on the key dynamic features of the process. Such information would be beneficial for any future career in Bio-manufacturing companies. Students are encouraged to promote an interactive environment for exchange of information.
|Assumed Knowledge:||It is assumed that students have a general knowledge of: MATH1001 Differential Calculus MATH1003 Integral Calculus and Modelling|
|Additional Notes:||This course is for Master degree students and also is offered as an elective course for fourth year students. Some lectures my be given by a guest lecturer.|
A/Prof Dehghani, Fariba
Dr Kavanagh, John
|T&L Activities:||Tutorial: There will be tutorial after each lecture(week 1-9) in the computer lab. It is expected that students work in a group of two and submit the tutorials to the tutor.
Independent Study: Students are expected to spend time for ‘self directed learning’ outside the specified contact periods.
Project Work - own time: There will be about two projects and self assisted learning. Students are expected to spend about 2 hours of study outside the specified contact period. Groups are allocated to work for some projects.
Quiz: There will be a mid-semester quiz.
Attributes listed here represent the key course goals (see Course Map tab) designated for this unit. The list below describes how these attributes are developed through practice in the unit. See Learning Outcomes and Assessment tabs for details of how these attributes are assessed.
|Attribute Development Method||Attribute Developed|
|Application of conceptual material.
Ability to cope with change.
Projects are provided to promote problem solving skills of the students
|Design (Level 2)|
|The students will learn the fundamental aspects of statistics and mathematical modeling of bioprocesses, Problem solving skills, Collate correct information from different sources for decision making,
|Maths/Science Methods and Tools (Level 4)|
|The students will obtain the skills to conduct research independently in new area and promote their critical thinking.||Information Seeking (Level 3)|
|Team work, oral presentation, and writing report were designed to improve communication skills of the students.||Communication (Level 3)|
|The assessments will promote the student`s responsibily for their performance. Develops the skills and tools needed for engineering practice - systems understanding of large classes of behavior.
Understanding of social aspects of engineering.
Lifetime or self-directed learning skills.
|Professional Conduct (Level 1)|
For explanation of attributes and levels see Engineering & IT Graduate Outcomes Table.
Learning outcomes are the key abilities and knowledge that will be assessed in this unit. They are listed according to the course goal supported by each. See Assessment Tab for details how each outcome is assessed.Design (Level 2)
Assignment: tutorials will be given each week on the basis of the thoroughness of students attempt and the correctness of the answer.
Assignment: The assignments will involve a self-study module and the aims are to encourage revision during the course, allow students to determine their progress in different subjects, and to gain an understanding of the learning expectations of the course.
Project: Real-life projects will be given to each group of 2 to 4 students to promote analytical, modeling and computer skills acquired during the course.
Quiz: There will be a mid-semester quiz.
|Policies & Procedures:||See the policies page of the faculty website at http://sydney.edu.au/engineering/student-policies/ for information regarding university policies and local provisions and procedures within the Faculty of Engineering and Information Technologies.|
Note: Students are expected to have a personal copy of all books listed.
Note that the "Weeks" referred to in this Schedule are those of the official university semester calendar https://web.timetable.usyd.edu.au/calendar.jsp
|Week 1||The role of statistics in biophysical processing, introduction|
|Assessment Due: Project|
|Week 2||Decision making for a single population|
|Week 3||Hypothesis Testing for two populations|
|Week 4||Analysis of Variance|
|Week 5||Analysis of discrete data|
|Week 6||Statistical Process Control,Regression and Correlation|
|Week 7||MATLAB Tool Box (statistical function)|
|Week 8||Practical applicaiton of MATLAB tool box for modeling|
|Week 9||Experimental design and using SPSS program|
|Experimental design and mid-session quiz|
|Week 10||modeling and Optimisation- group project|
|Week 11||Modeling and optimisation-group project|
|Week 12||Modeling and optimisation-group project|
|Week 13||Group presentation-submission of final project|
The following is a list of courses which have added this Unit to their structure.
This unit contributes to the achievement of the following course goals:
|Design (Level 2)||Yes||15%|
|Engineering/IT Specialisation (Level 4)||No||0%|
|Maths/Science Methods and Tools (Level 4)||Yes||30.01%|
|Information Seeking (Level 3)||Yes||15%|
|Communication (Level 3)||Yes||15%|
|Professional Conduct (Level 1)||Yes||15%|
|Project and Team Skills (Level 3)||No||10%|
These goals are selected from Engineering & IT Graduate Outcomes Table which defines overall goals for courses where this unit is primarily offered. See Engineering & IT Graduate Outcomes Table for details of the attributes and levels to be developed in the course as a whole. Percentage figures alongside each course goal provide a rough indication of their relative weighting in assessment for this unit. Note that not all goals are necessarily part of assessment. Some may be more about practice activity. See Learning outcomes for details of what is assessed in relation to each goal and Assessment for details of how the outcome is assessed. See Attributes for details of practice provided for each goal.