MATH1070: Frontiers of Computational Science

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Course Profile     2005

Summary

Course Code(s):	MATH1070
Unit Value:	#2
Contact Hours:	4 hours per week (2L1x2hourP)
Web:	http://www.maths.uq.edu.au/courses/MATH1070
Purpose:	MATH1070 is an introduction to the emerging discipline of Computational Science.  It focuses on the practical problems in science and technology that require a combination of mathematical and computational methods for their solution.  Computational skills will be developed through various computing packages and tools with a focus on some particular applications.  MATH1070 is designed particularly for students targeting the field of computational science within the BSc.

Teaching Staff

Professor Bernard Pailthorpe (Course Coordinator) Office: 69-721 Phone: (07) 3365-6131 Fax: (07) 3365-6136 Email: bap@uq.edu.au Consultation Times: TBA	Dr Marcus Gallagher Office: 47-502 Phone: (07) 3365 6197 Fax: (07) 3365 4999 Email: marcus@itee.uq.edu.au Consultation Times: TBA
Dr. Christine Beveridge Office:62-223E Phone: (07) 3365 7525 Fax:  (07) 3365 1699 E-mail: c.beveridge@botany.uq.edu.au Consultation Time: TBA

What is it?

Many of the most important problems in science can only be solved by using both mathematics and computation.  MATH1070 introduces this approach, by describing three areas:-

· Numerical solutions of equations.

· Applications to Physics and Chemistry.

· Computational Biology:-  models and energy flows in biological cells and ecosystems.

Why do it?

MATH1070 introduces you to computer solutions to contemporary science challenges.    It develops important practical skills in computational problem solving and modelling that are useful in later courses. You will learn to solve and graphically present science problems using MATLAB, or other appropriate software.

How does it work?

Students attend two lectures and one 2-hour practical computational laboratory each week. Assessment consists of assignments and an end of semester exam.

Where does it lead?

MATH1070 is designed particularly for students of computational science within the BSc. This new field develops graduates with advanced skills in large scale computational problem solving, modelling, and visualization, for science or engineering applications (e.g. biology, physics, chemistry, bioinformatics, earth science.)  This leads to MATH2200.

MATH1070 will also give students a background for computational biology. This leads to the second year course MATH2210, which introduces DNA sequencing and the modelling of molecular structures and biological systems.

What do I need?

MATH1070 has no prerequisites. However, you should have taken school Mathematics B or a mathematics course at UQ. MATH1070 does not assume any specific computing or programming skills.  MATLAB will be used in labs.

When is it available?

Second semester, every year.

Contact Advice

Computational Science Coordinator and MATH1070 Course Coordinator: Professor Bernard Pailthorpe, Room 69-721 (Old Computer Science Building), Ph 336-56131, Email bap@maths.uq.edu.au .

Assumed Background

There are no prerequisites, but you should have reasonable scores at school maths B, or in a UQ mathematics course.  We do not assume that you have any specific computing or programming skills.  Of course, during semester you may need to do some background reading in order to gain an understanding of the lecture material, or of the specific scientific problem being solved.

Resources

Textbook

There is no specified text for MATH1070.

Reference Texts

Students are not expected to purchase the following book, but may find it useful.  Copies of these books are available in the library.

"Assume a Spherical Cow",  J Harte (University Science Books, 1988)
" The Computational Beauty of Nature: computer explorations of fractals, chaos, complex systems and adaptation", G. W. Flake (MIT Press, 1998)

“The Golden Ratio: The Story of Phi, the Extra ordinary Number of Nature, Art and Beauty”, Mario Livio (Review, Headline Book Publishing, 2002)

“Supercomputing and the Transformation of Science”, W.J. Kaufmann III, L.L. Smarr (Scientific American Library, 1993)

Handouts

Handouts will be given in class.

Facilities

Students will have access to the PC’s in the mathematics computer laboratories (Rm-67-442 676-542).  This is for assignment work, and keeping up to date with Email announcements and Web and material.  Students will need to work in laboratories outside the scheduled times in order to complete their assignment work. 

Consultation

Consultation times for the teaching staff are given above.

Distribution of Notices

Notices to students will usually be delivered in lectures and electronically (e.g., by email and web-site update).

Web

The course web page is  http://www.maths.uq.edu.au/courses/MATH1070

Teaching and Learning

Lectures

There are two hours of scheduled lectures each week, and it is expected that students will attend all lectures.  Lectures schedule below will be completed in due course.  Check MySiNet for any late changes.

Lecture 1	Monday	9.00am – 9.50am	Room 68-214	Weeks 1 - 13
Lecture 2	Wednesday	11.00am – 11.50am	Room 68-214	Weeks 1 - 13

Practicals

Students should sign-up for one of the practicals on SI-net, and they should attend this practical every week.  In this course practicals start in week 1.  For weeks 1 to 9, all pracs will be held Room 47A-250. For weeks 10, 11 and 12 pracs will be held in Room 67-542.  Check MySiNet for any late changes. 

Prac Session	Monday	2-00pm – 3.50pm	Bldg 47A, Rm 250	Weeks 1 – 9 and 13
			Building 67, Rm 542	Weeks 10,11 and 12

Attendance

It is expected that everyone will attend all lectures and practicals.  The lectures and pracs have been carefully designed to help learning the course material.  If you miss a session, it will be more difficult to understand later topics.  It is up to you to find out what happened at any class session that you miss.

Pracs cover additional examples and problems, and develop key skills in actual implementation.  This is an essential component of the course. 

Support for Students with a Disability

Any student with a disability who may require alternative academic arrangements in the course is encouraged to seek advice at the commencement of the semester from a Disability Adviser at Student Support Services.

Teaching Plan

Lecture topics will roughly follow the schedule on the lectures page.  This may be changed slightly from time to time.  Significant changes will be announced by email.

Assessment

Assignments

Assignments will be available at the Prac Session and on the web in the week before they are due.  Some assignments may be available earlier.  Assignments will be based on the material covered during lectures, and will reinforce the practical skills and experience developed through attending the practical sessions.

The first assignment will test your understanding of introductory programming in Matlab. It will contribute 15% towards your final assessment, and will be due at 4pm on Friday 19th August.

Assignments 2 and 3 will require you to answer several questions on relating to the lectures and prac sessions on complex systems.  Questions will cover decentralised systems, cellular automata, RBN dynamics and networks.  Assignment 2 will contribute 15% towards your final assessment, and will be due at 4pm on Friday 9^th September.  Assignment 3 will contribute 10% towards your final assessment, and will be due at 4pm on Friday  23rd September

Assignments 4 and 5 will cover the material developed in the last section of the course.  Each is worth 10%

.

Final Examination

A two hour, final examination will be held during the final examination period.  This will be a 2 hr closed book exam with no choice of question.  Calculators without advanced text storage capabilities (i.e. no `qwerty’ keyboard) will be permitted; but only simple arithmetic will be needed in the final exam.  This exam will contribute 40% towards your final assessment.  It is essential to obtain at least 50% of the marks on the final examination in order to pass MATH1070.

Determination of Final Grade

To obtain the final grade for MATH1070, the marks for each citem will be weighted as above and added to give a final mark out of 100.  People will receive a grade from 1 to 7 if their mark is above the following cut offs,

Mark	85	75	65	50	45	20	0
Grade	7	6	5	4	3	2	1

except a grade of 4 will only be awarded to people who get at least 50% in the final examination.  If the mark on the final examination is less than 50%, the grade will be reduced to 3.

Assessment Policies

Submission

Submission of the assignments will be made to the lecturer or tutor after the prac session prior to the due date. Your assignment submission must be accompanied by a signed coversheet declaring that the submission is your own, original work.  Cover sheets can be downloaded from the web, or will be available in tutorials.  Electronic assignment submission is not available in this course. 

Late Submission

All assignments are due at 4pm on the nominated Friday.  No material will be accepted after this time.  In the absence of a medical certificate or other documentary evidence of a serious problem, late submission will result in the loss of all credit for that piece of work. 

Students who miss assignments through bereavement or ill health should document their problems and discuss this with the coordinator.  They may be given an average mark for missed assignments, or a short extension.

Special Exam

If a student is unable to sit the final examination for medical or other adverse reasons, they can and should apply for a special examination.  Applications made on medical grounds should be accompanied by a medical certificate; those on other grounds must be supported by a personal declaration stating the facts on which the application relies.  Applications for special examinations must be made through the Student Centre.  More information on the University’s assessment policy may be found
http://www.uq.edu.au/hupp/contents/view.asp?s1=3&s2=30&s3=5
EPSA Faculty policy on the award of special exams may be found via the Faculty Guidelines from the EPSA student page http://www.epsa.uq.edu.au/index.html?id=9329&pid=7564

Supplementary Examinations

A supplementary examination may be awarded in one course to students who obtain a grade of 2 or 3 in the final semester of their program and require this course to finish their degree.  You should check the rules for your degree program for information on the possible award of supplementary examinations.  Applications for supplementary examinations must be made to the Director of Studies in the Faculty.

EPSA Faculty policy on the award of supplementary exams may be found via the Faculty Guidelines from the EPSA student page http://www.epsa.uq.edu.au/index.html?id=9329&pid=7564

Feedback

Marked assignments will be returned to students during scheduled laboratory classes.  Every effort will be made to provide timely feedback on all progressive assessment. This may include general feedback in class or individual feedback at a consultation.  Examination scripts are also viewable after the release of semester results.

Students may peruse examinations scripts and obtain feedback on performance in a final examination provided that the request is made within six months of the release of final course results.  After a period of six months following the release of results, examination scripts may be destroyed.  Information on the University’s policy on access to feedback on assessment may be found at http://www.uq.edu.au/hupp/contents/view.asp?s1=3&s2=30&s3=5

EPSA Faculty policy on assessment feedback and re-marking may be found at http://www.epsa.uq.edu.au/index.html?id=7674&pid=7564

Academic Merit, Plagiarism, Collusion and Other Misconduct

The Schools and the wider academic community in general take academic integrity and respect for other persons and property very seriously.  In particular, the following behaviour is unacceptable:

• Submission of plagiarised work, i.e. work that contains content copied from an unacknowledged source.
• Submission of work without academic merit,  i.e. work that adds little or nothing to material available from reference sources such as textbooks, websites, etc., even where this is appropriately acknowledged.
• Engaging in collusive behaviour, i.e. inappropriate working together with other students where individual work is required, or working with people outside your team where team work is required.
• Copying work done by other students.
• Failing to adhere to the School's regulations concerning behaviour in laboratories, in particular occupational health and safety regulations.

Penalties for engaging in unacceptable behaviour can range from cash fines or loss of grades in a course, through to expulsion from the University.

You are required to read and understand the ITEE School Statement on Misconduct, available on the ITEE website at: http://www.itee.uq.edu.au/about/student-misconduct.jsp

If you have any questions concerning this, please contact your lecturer in the first instance.

Assessment criteria

Each assessment item will be graded on the extent to which it shows students have achieved the course objectives.

To earn a grade of 7, a student must demonstrate an outstanding level of achievement of all the course objectives. This will include all of the following:-

· Completely correct understanding of the appropriate theory, computational techniques of solution, and their implementation; including a complete understanding of their limitations and substantial insights into possible extensions and improvements.

· Completely correct application to solve novel problems, including a complete understanding of the limitations of mathematical models and substantial ideas for possible improvements.

· An outstanding ability to explain, justify, and present mathematical and computational solutions, including substantial insights into new aspects of the problem.

To earn a grade of 6, a student must demonstrate an excellent level of achievement of all the course objectives. This will include all of the following:-

· Completely correct understanding of the appropriate theory, computational techniques of solution, and their implementation; including an understanding of their limitations and some suggestions for possible extensions and improvements.

· Completely correct application to solve novel problems, including an excellent understanding of the limitations of mathematical models and some plausible suggestions for possible improvements.

· An excellent ability to explain, justify, and present mathematical and computational solutions, including insights into new aspects of the problem.

To earn a grade of 5, a student must demonstrate a sound level of achievement of the course objectives.  This will include all of the following:-

· Almost completely correct understanding of the appropriate theory, computational techniques of solution, and their implementation; including a good understanding of the most important limitations.

· Substantially correct application to solve familiar problems, including a good understanding of the most important limitations of mathematical models.

· A sound ability to explain, justify, and present mathematical and computational solutions, including an occasional insight into new aspects of the problem.

To earn a grade of 4, a student must demonstrate an basic level of achievement of the course objectives.  This will include all of the following:-

· Essentially correct understanding of the appropriate theory, computational techniques of solution, and their implementation; including an understanding of the most important limitations.

· Essentially correct application to solve simple familiar problems, including a basic understanding of the most important limitations of mathematical models.

· A mostly adequate ability to explain, justify, and present mathematical and computational solutions.

To earn a grade of 3, a student must demonstrate a basic level of achievement of almost all the course objectives, marred by only a small number of fundamental difficulties in a few parts.  The student must have demonstrated the ability to earn a grade of 4 with further work.

To earn a grade of 2, a student must demonstrate a basic level of achievement of some of the course objectives in some parts.

To earn a grade of 1, a student must enrol in the course and submit an item of assessment.

Graduate Attributes Developed

The University of Queensland has defined a set of graduate attributes to specify broad core knowledge and skills associated with all undergraduate programs (http://www.uq.edu.au/hupp/contents/view.asp?s1=3&s2=20&s3=5). This course addresses these attributes as follows:

Attribute	Contributions from this Course
In-depth knowledge of the field of study	A well-founded knowledge of the field of study through the study of the theory underlying 3 important areas of computational science in lectures and practicals and solving problems in a range of applications. An understanding of how other disciplines relate to the field of study through studying examples and solving problems from a broad array of disciplines and attending invited lectures to show how computational science can be applied in many areas. An international perspective on the field of study through studying recent problems and applications that have attracted international teams of researchers to the emerging descipline of computational science.
Effective Communication	The ability to collect, analyse, and organise information and ideas, and to convey those ideas clearly and fluently through explaining, justifying, ad presenting solutions to problems. The ability to interact effectively with others in order to work towards a common outcome through cooperative learning strategies in practicals. The ability to select and use the appropriate level, style and means of communication through presenting solutions to problems using written exposition, mathematical reasoning, tables, graphs, and advanced visualization technologies. The ability to engage effectively and appropriately with information and communication technologies:- through use of a range of appropriate software.
Independence and Creativity	The ability to work and learn independently through independent problem solving. The ability to generate ideas and adapt innovatively to changing environments through solving a progression of increasingly complex problems in the emerging and constantly changing discipline of computational science.
Critical Judgement	The ability to define and analyse problems:- by taking a succession of real-world problems, reducing them to their essential mathematical and computational components, and applying systematic problem solving techniques. The ability to apply critical reasoning to issues through independent thought and informed judgement:- by developing models to explore the issues and performing computational experiments to test hypotheses. *  The ability to evaluate opinions, make decisions and reflect critically on the justifications for decisions through applying models, and acknowledging and experiencing their limitations.
Ethical and Social Understanding	An appreciation of the philosophical and social contexts of the discipline through understanding how the emerging discipline of computational science effects and is effected by other disciplines. A knowledge and respect of ethics and ethical standards in relation to a major area of study:- through the experience of a discipline where the concepts of right and wrong are supported by universal and absolute standards, and an understanding of the limitations of computational models. A knowledge of other cultures and times and an appreciation of cultural diversity:- through tutorial participation in a subject taken by students with diverse backgrounds and interests.

MATH1070 Web Page.