School of Computing, Electronics and Mathematics Semester Abroad Scheme

The School of Computing, Electronics and Mathematics (SoCEM) invite BTech and BE students in their eighth semester who are taking courses in the areas of electronics; robotics; computer science or electrical engineering to join the second semester in Plymouth in January/February 2019 to complete a project alongside our own BEng students.

This year, nominated students will be able to apply for one of our proposed projects listed below. 

The application process is competitive and applicants will be judged via the following criteria: 

• previous academic performance (academic transcripts must be supplied)

• your personal statement (you must explain why you want to apply for one of our projects and how it aligns with your own academic background, interests and career prospects)

• quality of application.
  

We will not accept applications for projects that are not listed on this page.

How to apply

To apply please complete the application form along with the following supporting documents:

• personal statement – acceptance of your application will be based mainly on the quality of your application. This should express why you have applied for your selected project and how your current studies, academic background and career prospects match with your selected project

• your third, fourth, fifth and sixth (seventh if possible) semester results

• copy of the photo page of your passport

• evidence of English Language (IELTS or Indian Senior School Certificate Examination).

Project 1

RoQ/DDoS detection and mitigation system for IoT devices.

The grand vision of the Internet of Things (IoT) is to establish a whole new ecosystem comprised of heterogeneous connected devices that communicate to deliver environments making our living, cities, transport, energy, and many other areas more intelligent. Earlier forecasts on the number of connected devices estimated their number around 50 billion by 2020.

Such technological evolution is also making our society vulnerable to new forms of threats and attacks exploiting the complexity and heterogeneity of IoT networks, therefore rendering cyber-security amongst the most important aspects of a networked world.

The proposed research aims to explore IoT vulnerabilities and propose and innovative gateway that will utilise Deep Learning and deep packet inspection in order mitigate DDoS/RoQ attacks.

Supervisor: Dr Stavros Shiaeles

Project 2

Malware detection and mitigation system for IoT devices

The grand vision of the Internet of Things (IoT) is to establish a whole new ecosystem comprised of heterogeneous connected devices that communicate to deliver environments making our living, cities, transport, energy, and many other areas more intelligent. Earlier forecasts on the number of connected devices estimated their number around 50 billion by 2020.

Such technological evolution is also making our society vulnerable to new forms of threats and attacks exploiting the complexity and heterogeneity of IoT networks, therefore rendering cyber-security amongst the most important aspects of a networked world.

The proposed research aims to explore IoT vulnerabilities and propose and innovative gateway that will utilise Deep Learning and deep packet inspection in order mitigate DDoS/RoQ attacks.

Supervisor: Dr Stavros Shiaeles

Project 3

Security Education using Gamification

Mobile app development or web development on implementing and designing suitable games for educating various age groups (ie children, adults, older people) on internet safety, passwords and social engineering.

Skills required: iOS and/or android mobile app development, Java (or any other suitable web development skills).

Supervisor: Dr Ismini Vasileiou

Project 4

Learning Analytics in Higher Education

To implement an application (either mobile or web based) on collating and analysing student data collected by a department and/or institution. The project will aim to understand the relevance of the student data (ie attendance, grades, ebooks etc) in order to help the department or the institution to develop their strategies on supporting their students further.

Skills required: Software engineering skills, data science (Preferably knowledge of R or any other similar/relevant application).

Supervisor: Dr Ismini Vasileiou

Project 5

LabView based measurements of electronic component

This project will interface MyDAQ with LabView to collect current-voltage data from electronic components. The data collected will contribute to our research on graphene biosensors.

Supervisor: Dr Shakil Awan

Project 6

Graphene Biomedical Sensors

This project will explore fabrication and testing of graphene sensors for a range of biomedical applications (Alzheimer’s, Cancer and heart related conditions). The successful applicant will work as part of a team of students and research staff with access to state-of-art instruments in a Class-100 Clean Room, such as Parameter analysers, atomic force microscope, Raman spectroscopy etc. This is a challenging project and requires the applicant to be familiar with accurate electrical current, voltage, resistance measurements and software tools such as MatLab, Origin, Excel and preferably LabView also (but not essential as training can be provided).

Skills required: MatLab, Origin, Excel and preferably LabView

Supervisor: Dr Shakil Awan

Project 7

Analysis of Twitter Trending Topics

Social media companies, such as Twitter, deal with petabytes of information on a daily basis. Regrettably, people often find it difficult to cope with the overwhelming stream of data published by millions of users worldwide. Scientists have already worked out ways to identify Twitter trending topics, as a means to index information and make sense of it. However, we know little about the impact on trending topics of various intrinsic factors associated with the Twitter ecosystem. For example, anecdotal evidence suggests that trending topics are characterised by highly polarised tweets, or that large audiences typically host the emergence of trending topics. However, no study has yet addressed these issues formally. To remedy this situation, we will investigate the nature of trending topics in this project. We will uncover any correlation between sentiment polarity and trending topics (and confirm whether the strength of the polarity drops as the trending topics fade away). Similarly, we will run experiments to determine the relationship between the size of a Twitter audience and the rise of trending topics.

Skills required: Good programming skills are required. Knowledge of a high level programming language (such as Java, C# or Python) is indispensable. Knowledge of databases (either relational or non-relational) is desirable, but not indispensable. Ability to understand and convey complex information is expected. Help will be provided throughout the project, but students will be required to develop their own software, based on algorithm descriptions.

Supervisor: Dr Marco Palomino

Project 8

SDN-Assisted Delivery of Adaptive Video Streaming

Over the recent years, real-time Internet applications and services (e.g. VOIP, Video streaming, and online gaming) have been increasing at a tremendous rate. The increasing consumption of multimedia services and the demand of high quality services from customers pose challenges to service providers and mobile operators in terms of Quality of Service/Quality of Experience (QoS/QoE) control and management. Recently, Software-defined networking (SDN) has emerged as a network model that decouples forwarding elements (e.g. switches, routers, etc.) from control features and provides an efficient way for resources monitoring and utilization, centralized network management, and network programmability. Acquiring a guaranteed QoS and QoE for network traffic and end user by using SDN is drawing the attention of industrial and academic sectors. Therefore, there is a need for QoS/QoE control and management solutions pertaining to programmable networks, cost reduction of IT systems, high speed and reliable transfer of heterogeneous data over software defined and virtualized infrastructures. The main objective of this project is to develop an SDN-based frameworks for improving the received quality at the end-users. The developed framework should be able to provide automated functionality and adjust dynamically to changing network conditions (e.g., during congestion state) and allow for proactive network management regardless of any situation within the network or the end user’s side.

Skills required: SDN, Python, JavaScript, Websocket, RESTful programming, Node.js & WebSocket, HTML5. Also, it would be useful if the applicants have the following skills: SDN Ryu/Opendayligh controller, DASH.js, WebRtc, Video encoding, TCPdump, Wireshark

Supervisor: Dr Bogdan Ghita

Project 9

Biomemristors Network for Biocomputing

The Interdisciplinary Centre for Computer Music Research is a world-leader in developing biocomputers using electronic components grown out of biological material. The team has developed unprecedented biological memristor and an approach to using such a biomemristors to build interactive generative music systems. The memristor is a relatively less well-known electronic component regarded as a resistor with memory. This project is to implement a neural network of biomemristors, develop an algorithm for machine learning and test it with music data (e.g., MIDI files).

Skills required: Knowledge of Python, knowledge of microcontroller boards such as Arduino and/or Rasperry Pi, some understanding of music technology, neural network models and electronics.

Supervisor: Professor Eduardo R. Miranda

Project 10

Hybrid Memristive Circuits

The Interdisciplinary Centre for Computer Music Research has developed unprecedented biological memristor and an approach to using such a biomemristors to build interactive generative music systems. Biomemristors present more non-linear behaviour than silicon-based ones. This project is to develop experiments to understand of (a) how to control its non-linearity and (b) how to combine both types of biomemristors in the same circuit. The domain application of the experiments will be interactive music systems.

Skills required: Knowledge of Python, knowledge of microcontroller boards such as Arduino and/or Rasperry Pi, some understanding of music technology, benchmarking methods, and electronics.

Supervisor: Professor Eduardo R. Miranda

Project 11

Brain-Computer Music Interfacing for Prosthetic Hand

The Interdisciplinary Centre for Computer Music Research is a world-leader in the field of Brain-Computer Music Interfacing (BCMI). A BCMI systems uses electrical activity of the brain, referred to as EEG (short for electroencephalogram) to control musical systems, such as generative music software and digital sound synthesisers. The EEG is detected by means of electrodes placed on the scalp of a person. The main aim of our research is to enable people with severe motor impairment (e.g. paralysis of the limbs) to make music. This project is to develop a BCMI system to control a prosthetic hand to play a musical instrument such as a drum or a keyboard.

Skills required: Knowledge of Matlab and Python. Candidates should become familiar with the software OpenVibe (a brain-computer interface implementation tool) beforehand. Knowledge of signal processing is required to analyse the EEG.

Supervisor: Professor Eduardo R. Miranda

Project 12

Graphene / CNT Nanocomposite Polymer Thin Films

Design and adapt a magnetic stirrer as a controllable low speed spin coater for the fabrication of thin (1 micron) nanocomposite films. The load speed of the magnetic stirrer (< 100 rpm) is suitable for preparing thin nanocomposite films for sensor applications. Polymer-graphene nano composite films will use a piezoelectric polymer (PVDF) as the host matrix with small amounts (~ 5 % by weight) of graphene flakes or CNTs added to change the film’s properties. The films will be characterised using AFM, Raman and SEM. Films of one micron thickness can be polarised to make the piezoelectric and their suitability for sensing determined.

Skills required: This projects fall into the arena of nanotechnology and nanodevices and is particularly suitable for electrical and electronic engineering students.

Supervisor: Dr David Jenkins

Project 13

LabVIEW Controller for a Nanoparticle Measurement System

The Nanomaterials laboratory has a highly sensitive optical system – Surface Plasmon Resonance – for detecting very low concentrations of nanoparticles and micro-plastics. A new control system using LabVIEW is required to control the motors which synchronously move the laser (probe) and the detector with high accuracy and precision. The position signals are determined from a 14 bit optical encoder. The detection of NPs is based upon the measurement of the detected signal vs angle of a small angular range. Detection capability can be further enhanced by measuring the detected signal using a lock-in amplifier.

In this project the opto-mechanical system is fully functional. The LabVIEW controller software will enable some exciting measurements to be made, with many possibilities to become a co-author in high impact factor publication. This is excellent for your CV and will give added benefit to those wishing to do research after graduating.

Skills required: Knowledge of LabVIEW. This project falls into the arena of nanotechnology and nanodevices and is particularly suitable for electrical and electronic engineering students.

Supervisor: Dr David Jenkins

Project 14

Gelf’and Pinsker coding of relatively low noise narrowband ultrasound channels

Ultrasound transducers have very narrow band width resulting in low data rates for binary transmission. However the SNR is in some cases high, indicating the possibility of increasing the data rate through multilevel coding, equalisation or, more recently and more generally through side information (Gelf’and-Pinsker) known interference cancellation techniques. The project will practically measure a low noise ultrasound channel and propose novel and adequate interference cancellation techniques based on side information coded modulation. It is anticipated that the signal conditioning techniques proposed will be implemented and tested on an ultrasound transmitter/receiver based on embedded programming on an ARM processor board (STM). Ultrasound communications are rapidly gaining interest due to their biomedical and underwater applications. An immediate application of the proposed techniques would also be the communications lab for the BEng/BSc EEE/Robotics Stage 2.

Skills required: Embedded C programming and signal processing.

Supervisor: Dr Adrian Ambroze