Category Archives: Yr 3 Descriptions 2021/2022

Please click Older Posts at the bottom of the page and subsequent pages for further project descriptions.

Dimension Reduction and Classification Algorithms – Supervisor: Dr Andreas Artemiou

Title of Project: Dimension Reduction and Classification Algorithms

Code:
AA2122A

Supervisor:
Dr A. Artemiou

Project description:
Data mining and dimension reduction are two topics which receive great attention in the big data era we are in. There are a number of algorithms which were proposed to discuss data mining algorithms (like Support Vector Machines) and dimension reduction algorithms (like Sufficient Dimension Reduction). Recently, the two areas were combined to create new algorithms for dimension reduction in regression using ideas from the data mining literature. This created a class of new algorithms that perform very well and are able to do linear and nonlinear dimension reduction in a unified framework.
The project objective is to create first new algorithms for data mining by combining existing algorithms. The student will review the given literature and then derive results for new methodology for classification. The performance of the new algorithm will be evaluated using real datasets. Then, the algorithms will be used to perform dimension reduction to regression problems based on existing literature. Good programming skills are essential for this project. (In 2017-2018 a student work on this project and developed a modified version of SVM)

Project offered as a Double module.

Prerequisite 2nd year modules:
Definitely MA2500: Foundations of Probability and Statistics; MA2501: Programming and Statistics is helpful but not essential.

Recommended 3rd year module for concurrent study:
MA3505: Multivariate Statistics can be helpful but not required.

Number of students who can be supervised on this project:
1

Cavitation in nematic elastomer spheres – Supervisor: Dr A Mihai

Title: Cavitation in nematic elastomer spheres

Code: AM2122A

Project Description:

Nematic liquid crystal elastomers are advanced multifunctional
materials that combine the exibility of polymeric networks with the ne-
matic structure of liquid crystals. Due to their complex molecular architec-
ture, they are capable of exceptional responses, such as large spontaneous
deformations and phase transitions, which are reversible and repeatable
under certain external stimuli (e.g., heat, light, solvents, electric or mag-
netic elds). Their accurate description requires multiphysics modelling
combining elasticity and liquid crystal theories.

In particular, instabilities in liquid crystalline solids can be of potential
interest in a range of applications. This project focuses on the cavitation
instability where a void forms at the centre of a nematic sphere under
radial symmetric tensile load. Assuming an initially unit sphere described
by a simple neoclassical model for ideal nematic elastomers, the aim is
to determine the critical load for the onset of cavitation, and to verify
if the associated bifurcation from the trivial solution where the sphere
remains undeformed is supercritical, i.e., if the cavity radius increases
as the applied load increases. A comparison with similar phenomena in
purely elastic spheres will also be performed.

Project offered as a Double module.

Type: 20 credits

Supervisor: Dr Angela Mihai

Prerequisite 2nd year modules: Real Analysis, Calculus of Several Vari-
ables, Linear Algebra

Prerequisite 3rd year modules for concurrent study: Partial Differential
Equations, Methods of Applied Mathematics, Finite Elasticity

Maximum number of students: 1

Develop Innovative Methods for Teaching mathematics in Primary School – Supervisor: Dr. F. Dragoni & Dr. M. Pugh

Title of project:
Develop Innovative Methods for Teaching Mathematics in Primary School

Code:
FD2122A

Supervisor: Dr F. Dragoni & Dr. M. Pugh

Project description:
1-The project consists in developing an extra-curricular mathematical subject or to be introduced in primary school, at all levels from Reception to Year 6.
The student will need to choose and develop the subject as a topic across all years, and design practical activities that will be used to teach it.
We will contact primary schools to find one willing to participate in the project, and the student will liaise with the school arrange to teach the planned activities to the pupils. It is proposed that these activities would take place during the week around March 14th (Pi-Day).
The student will write a report which discusses the mathematical content chosen, the design of these activities, along with reflection on the success of these activities and recommendations for improving them for future years.
Some possible subjects to develop could be:
– the idea of dimension, from Euclidean space to the fourth dimension (Flatland could be an interesting book to develop activities especially for the youngest children);
– functions, including sets, domain, basic properties of functions, etc;
– limits (extremely challenging);
– any other subject proposed by the student.
2-Alternatively the project can focus on develop innovative methods to teaching numerical skills and/or problem solving in primary schools.
In this direction some possible subjects are developing board games for advance numerical skills and problem solving or explore how to use sport and playing activities to strength the mathematical curriculum in primary schools across Wales.
Also in this case the project will consist in a first part where the student will need to get familiar with the literature and the Welsh math curriculum, a second part where she/he will develop specific activities, a third part where these activities will be delivered to a selected group of primary school pupils and a final part where the student will collect feedback on the activities delivered and reflect on them, implementing when necessary modifications.

Project offered as double module, single module, or both:
Double

Prerequisite 2nd year modules:
None

Recommended 3rd year module for concurrent study:
None

Number of students who can be supervised on this project:
1

Frobenius algebras – Supervisor: Dr A Ros Camacho

Title of Project: Frobenius algebras

Code: ARC2122A

Supervisor: Dr A Ros Camacho

Project Description: Frobenius algebras are an interesting family of algebras
that play a crucial role in research topics of mathematical physics. In this
project, we will study them and its properties, compute several examples
of these and see how they arise in the study of topological and conformal
eld theory.

Project offered as a Double module.

Prerequisite: 2nd year modules: Linear Algebra II, Algebra 1: Groups

Prerequisite: 3rd year modules for concurrent study: Algebra 2:
Rings, Algebra 3: Fields

Maximum number of students: 2

Type: algebra, mathematical physics

Optimeiddio Systemau Ciwio – Goruchwyliwr: Dr Geraint Palmer

Teitl y project:   Optimeiddio Systemau Ciwio

Code:  GP2122A

Goruchwyliwr:   Dr Geraint Palmer

Disgrifiad:
Fe ellir modelu systemau ciwio mewn gwahanol ffyrdd, yn analytig trwy ddiffinio cadwynau Markov, neu trwy efelychiad cyfrifiadurol. Mae’r dulliau hyn hefyd yn gallu cael eu hymestyn a’u defnyddio ar gyfer optimeiddio. Gallwn ymestyn cadwynau Markov i brosesau penderfynu Markov (Markov decision processes), a’i ddatrys gyda dulliau rhaglennu deinameg (dynamic programming); a gallwch ychwanegu algorithmau dysgu atgyfnerthol (reinforcement learning) i efelychiadau cyfrifiadurol.

Bydd y prosiect hwn yn edrych ar ryw system ciwio benodol a ellir ei optimeiddio, a defnyddio’r dulliau hyn i archwilio i mewn i’r strategaethau gorau ar ei chyfer. Er enghraifft, pryd yw’r amser gorau i ychwanegu gweinyddion ychwanegol? Pryd yw’r amser gorau i ddargyfeirio cwsmer i weinydd cyflymach, ond fwy costus? Pa mor wael oes angen i’r system fod cyn gwrthod cwsmeriaid newydd?

Rhagofynion modiwlau’r ail flwyddyn:  Bydd MA2601 yn ddefnyddiol iawn, ond nid yw’n hanfodol. Bydd angen fod yn gyfforddus yn defnyddio Python. 

Nifer o fyfyrwyr y gellid eu goruwchwylio am y project hwn: 2

The Arithmetic-Geometric Mean and Elliptic Integrals – Supervisor: Prof. K.M. Schmidt

Title of project:
The Arithmetic-Geometric Mean and Elliptic Integrals

Code:
KMS2122A

Supervisor: 
Prof. K.M. Schmidt

Project description:
The Arithmetic-Geometric Mean is a function, defined via a limit process by Gauss after playing with the two concepts of mean which compose its name. This function turns out to be intimately connected with elliptic integrals and, since its defining limit converges with breathtaking speed, provides an efficient method for the calculation of such integrals, which resist application of the usual techniques of calculus. Moreover, the connection of elliptic integrals with the number pi gives rise to very fast converging algorithms for the calculation of this number to millions of decimal digits.

In the project, the properties of the arithmetic-geometric mean and its relation to elliptic integrals are reviewed, working towards an understanding of the Salamin algorithm for pi.

Prerequisite 2nd year modules:
MA2006 Real Analysis

Number of students who could be supervised for this project:
1

Analysing the distribution of GARCH innovations – Supervisor: Dr. Kirstin Strokorb

Title of project:
Analysing the distribution of GARCH innovations

Code:
KS2122A

Supervisor: 
Dr. Kirstin Strokorb

Project description:
When modelling financial time series with GARCH(1,1) processes, the distribution of the GARCH innovations plays a key role in dynamic risk managment. For instance, choosing either Student-t innovations or normal innovations as a modelling approach can lead to over- or underestimation of potential risks. The literature often suggests that Student-t innovations seem to be more appropriate in most practically relevant situations. However, it has also been noted that, even when we simulate a GARCH time series with normally distributed innovations and re-estimate the innovations using standard MLE methods, the re-estimated innovations typically resemble more a Student-t sample rather than a normal one. This indicates that standard methods are typically not robust and can lead to misspecification. Sun and Zhou (2014) develop a statistical test that is based on analysing ”implied tail indices” in order to make it easier to distinguish between Student-t and normal innovations.

Guiding questions:
The aim of this project is to understand the main reasoning of this testing procedure, to implement it using statistical software, to study its performance and robustness in simulated scenarios and finally, to analyse the innovations of some real financial time series using the Sun and Zhou (2014) procedure.

Main literature suggestion (starting point):
• P. Sun and C. Zhou (2014). Diagnosing the distribution of GARCH innovations. Journal of Empirical Finance, 29, 287-303.
• conceivably references therein as needed

Project offered as double module, single module, or both:
Single

Prerequisite Modules:
Foundations of Probability and Statistics (MA2500)
Econometrics for Financial Mathematics (MA2801)
Programming and Statistics (MA2501)

Number of students who could be supervised for this project:
1

Arithmetic Functions and the Riemann Zeta Function – Supervisor: Dr M. C. Lettington

Title of project:
Arithmetic Functions and the Riemann Zeta Function
Code:
MCL2122A
Supervisor: 
Dr. M. C. Lettington
Project description:

Project offered as double module, single module, or both:
Double
Prerequisite and Recommended 2nd year modules:
MA2011 Introduction to Number Theory I
Recommended 3rd year modules for concurrent study:
MA3011 Introduction to Number Theory II
Number of students who could be supervised for this project:
1

Eigenvalue Problems for (Large) Matrices – Supervisor: Prof. M. Marletta

Title of Project:
Eigenvalue Problems for (large) Matrices
Code: MM2122A
Supervisor: Professor Marco Marletta
Project description:
This project is about solving the matrix eigenvalue problem Au = λu. The
ultimate aim is to deal with the case when A is a large sparse matrix, but the
student will rst study methods which are used for full matrices. For sparse
matrices, it will involve studying numerical methods which exploit the sparsity
patter, together with possible additional properties such as being Hermitian.
Many of the algorithms to be studied are described in `Matrix Computations’
by Golub and Van Loan, and are implemented in software packages such as
LAPACK and ARPACK. The ability to programme in a suitable language such
as MATLAB or Python will be important. Special methods for PDEs will also
be studied if time permits.
Prerequisite 2nd year modules:
None
Recommended 3rd year module for concurrent study:
None
Number of students who can be supervised on this project:
1