COMP3204 Computer Vision

Module Overview

The challenge of computer vision is to develop a computer based system with the capabilities of the human eye-brain system. It is therefore primarily concerned with the problem of capturing and making sense of digital images. The field draws heavily on many subjects including digital image processing, artificial intelligence, computer graphics and psychology.

This course will explore some of the basic principles and techniques from these areas which are currently being used in real-world computer vision systems and the research and development of new systems.

Objectives:

To develop the students' understanding of the basic principles and techniques of image processing and image understanding.
To develop the students' skills in the design and implementation of computer vision software

Aims & Objectives

Aims

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

Human and computer vision systems
Current approaches to image formation and image modelling
Current approaches to basic image processing and computer vision

Subject Specific Intellectual

Having successfully completed this module, you will be able to:

Analyse and design a range of algorithms for image processing and computer vision
Develop and evaluate solutions to problems in computer vision

Subject Specific Practical

Having successfully completed this module, you will be able to:

Implement basic image processing algorithms

Syllabus

The human eye-brain system as a model for computer vision
Image formation: sampling theorem, Fourier transform and Fourier analysis
Image models
Basic image processing: Sampling and quantisation, Brightness and colour, Histogram operations, Filters and convolution, Frequency domain processing
Edge detection
Boundary and line extraction
Building machines that see: constraints, robustness, invariance and repeatability
Fundamentals of machine-learning: classification and clustering
Understanding covariance, eigendecomposition and PCA
Feature extraction
Interest point detection
Segmentation
2-D Shape representation
Local features
Image matching
Large-scale image search and feature indexing
Understanding image data and performing classification and recognition
3D vision systems
Recovering depth from multiple views
Practical examples, including: biometric systems (recognising people), industrial computer vision, etc

Learning & Teaching

Learning & teaching methods

Activity	Description	Hours
Lecture	Lectures and demonstrations of material	24
Tutorial	Students develop and present implementations of basic material	12

Assessment

Assessment methods

Method	Hours	Percentage contribution
Working with OpenIMAJ to achieve basic computer vision analysis	-	10%
Build basic technique	-	10%
Group coursework	-	20%
Exam	2 hours	60%

Referral Method: By examination and a new coursework assignment

Share this module Facebook Twitter Weibo

COMP3203 Serious Games

Module Overview

The aim of this module is to introduce students to the field of learning design and Serious Games and to provide students with practical experience of the design, development, delivery and evaluation of a modest game-based e-learning activity.

Aims & Objectives

Aims

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

Identify key concepts and principles in learning theory and cognitive psychology that underpin teaching, learning, and information processing
Identify the principles underlying the systems engineering of instructional materials and environments
Identify the elements of a serious game

Subject Specific Intellectual

Having successfully completed this module, you will be able to:

Analyse the instructional design of a series of learning activities in a game
Design a serious game to achieve a specified objective by following an instructional systems design method

Transferable and Generic

Having successfully completed this module, you will be able to:

Combine conflicting theories and requirements to develop an effective serious game

Syllabus

The instructional systems engineering (ISE) development lifecycle and its application to the analysis, design, production, and evaluation of instructional materials and serious games.
Key pedagogical components of instructional materials, and serious games.
Key technical components of serious games: Data structures; Games Engines; User Experience.
Tools and techniques for the analysis, design, production, and evaluation of serious games.

Learning & Teaching

Learning & teaching methods

Activity	Description	Hours
Lecture		36
Computer Lab		12

Assessment

Assessment methods

Concept of a Serious Game: Students individually design a serious game.

Prototype Serious Game: Students in groups design and develop a small prototype serious game.

Class Test: Supervised unseen restricted-time open-book individual exercise (detailed case study, short-answer and multiple-choice question), 90 minute duration.

Method	Hours	Percentage contribution
Concept for a Serious Game	-	30%
Prototype for a Serious Game	-	40%
Class test	-	30%

Referral Method: By set coursework assignment(s)

Share this module Facebook Twitter Weibo

ELEC3207 Nanoelectronic Devices

Module Overview

This module aims to provide an in-depth understanding of complimentary metal oxide semiconductor field effect transistors (CMOS) device physics and of the process flows used to fabricate CMOS transistors. It will discuss all important issues related to scaling down the transistor size into the nanometer regime, such as high-k dielectrics and FINFETs. The teaching will be complemented with a finite element simulation of the MOS scaling which will bring into practice many of the above improvements.

Aims & Objectives

Aims

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

Understand the fundamental device physics of semiconductors.
Understand the operation principle of CMOS transistors.

Subject Specific Intellectual

Having successfully completed this module, you will be able to:

Construct the process flows to fabricate CMOS transistors.

Subject Specific Practical

Having successfully completed this module, you will be able to:

Simulate the performance of CMOS transistors

Syllabus

Nanoelectronics

Technology roadmap of nano-electronics (Moore's law)

Scaling of devices and technology jump

Energy band structure in Silicon

Metal Oxide Semicoductor Field Effect Transistors (MOSFET)

Basic MOSFET Operation

Threshold Voltage and Subthreshold Slope

Current/voltage characteristics

Finite Element Modelling of MOS

Advanced CMOS transistors scaling

Challenge of the CMOS technologies

High-k dielectrics and Gate stack

Future interconnect

FINFET and architecture

Design for Variability

Mobility enhancement

Learning & Teaching

Learning & teaching methods

Activity	Description	Hours
Lecture		24
Computer Lab		12

Assessment

Assessment methods

Students can get good experiences by simulating the MOSFET characteristics after learning the fundamental principles in the lectures. Simulations and lecturing are complementary each other, and students can get more insights in understanding the MOSFETs. The learning outcomes include the capabilities to simulate unknown new device performance for their future jobs in CMOS or even beyond-CMOS industries.

Method	Hours	Percentage contribution
SILVACO finite element simulation	-	30%
Exam	2 hours	70%

Referral Method: By examination

Share this module Facebook Twitter Weibo

ELEC3206 Digital Control System Design

Module Overview

To introduce the student to the fundamentals of control theory as applied to digital controllers or sampled data control systems in general. To familiarise the student with the use of the MATLAB Control Toolbox.

Aims & Objectives

Aims

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

z transform analysis of sampled data feedback loops
stability theorems and root locus techniques
A suite of techniques for digital controller design
Optimal control design method

Syllabus

Introduction
Basics of z transform theory
- inverse z transform
- convolution
- recursion relation
- realisability

Sampling and reconstruction of signals
- zero order hold/D->A conversion
- Shannon's sampling theorem; aliasing and folding
- choice of the sampling period in sampled-data control systems
- pulse transfer function and analysis of control systems
- mapping of poles and zeroes

Case study: PID digital control

Continuous-time state-space systems and their discretization
- controllability and observability under discretization
- intersample behaviour

Realization theory
- canonical forms
- minimality
- internal- and BIBO-stability, and relation between the two

Controller design via pole placement
- continuous-time-based design techniques
- deadbeat control

Case study: root-locus based digital control design

Observers and their use in state-feedback loops
- Observer-based controllers
- the separation principle
Optimal control design

Introduction to optimal control
Finite horizon LQR
Inifte Horzion LQR

Learning & Teaching

Learning & teaching methods

Activity	Description	Hours
Lecture		36
Tutorial		12

Assessment

Assessment methods

Method	Hours	Percentage contribution
Exam	2 hours	100%

Referral Method: By examination

Share this module Facebook Twitter Weibo

ELEC3205 Control System Design

Module Overview

This module aims

To develop skills for design of linear multivariable control systems by pole placement.
To introduce basic nonlinear system analysis and design methods.

Aims & Objectives

Aims

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

Design controller using frequency domain methods
Analyse linear dynamical systems by state space methods.
Derive state space representation from a given transfer function representation.
Check controllability/observability by rank test of the controllability/observability matrix.
Design pole placement state-feedback controller in the state space setting, also with observers in the loop.
Model, analyse, and synthesise nonlinear dynamical systems.
Derive state space representations for nonlinear systems from first principles.
Analyse stability of nonlinear autonomous systems by state space methods.
Analyse nonlinear input--output systems by describing functions.

Syllabus

Frequency Domain Methods for Controller Design

Lead-lag compensator
Introduction to loop shaping

State-space representations for linear systems

Transfer function canonical realisations
State space representations

Structural properties

Controllability and state transfer
Observability and state estimation

Multivariable control by pole placement

Pole placement by state feedback
Elements of optimal control

State estimation

Observer design by pole placement

Joint observer-controller schemes
Nonlinear systems and mathematical modelling
Introduction to the phase plane analysis method
Stability and Lyapunov analysis

Lyapunov indirect method
Lyapunov direct method
Lasalle’s Theorem

Describing functions
Nonlinear control system design

Design via linearisation
Design via feedback linearisation
Introduction to Lyapunov based design method

Learning & Teaching

Learning & teaching methods

Activity	Description	Hours
Lecture		36

Assessment

Assessment methods

Method	Hours	Percentage contribution
2 problem sheets, containing 3 questions each.	-	20%
	-	%
Exam	2 hours	80%

Referral Method: By examination

Share this module Facebook Twitter Weibo

ELEC3203 Digital Coding and Transmission

Module Overview

to expand knowledge of techniques for information transmission via discrete (digital) channels, which have a wide area of applications, ie distributed computer systems, instrumentation and control systems, as well as communication systems of all types.
to introduce the basic concepts and applications of information theory and show its importance.
to develop skills in communications performance evaluation and digital transmission system design.
to concentrate attention on the application of the various analytical techniques.
to link theoretical concepts with cutting edge industrial standards.

Aims & Objectives

Aims

Having successfully completed this module, you will be able to:

understanding essential building blocks in modern digital communications systems.
understanding techniques for improving the efficiency and reliability of multimedia information.
design and characterise digital transmission components and schemes using Monte Carlo simulation.
bridge theoretical analysis with practical simulations and prototypes
understanding various design trade-offs and practical implementation constraints

Syllabus

Information Theory
- information and entropy
- coding of memoryless sources: Shannon-Fano / Huffman coding
- sources with memory: Markov model
- coding of sources with memory
- channel model and information across channels
- average mutual information and channel capacity
Digital Modulation and Optimal Reception
- quadrature amplitude modulation
- optimal transmit / receive filtering
- ASK/PSK constellations, eye diagram
- channel distortions and their influence on reception
- synchronisation, equalisation
- adaptive equalisation
Source Coding
- linear and non-linear quantisation, companding
- rate-distortion theory, predictive coding
- prediction gain, parametric and analysis-by-synthesis speech coding
- inter-frame video coding, motion compensation
- intra-frame video coding, transform coding
Channel Coding
- convolutional coding
- Viterbi decoding
- block coding
- hybrid ARQ
Coding versus Modulation Tradeoff
- bandwidth and power trade-off plane
- bandwidth efficient and power efficient design
- trellis coded modulation
- bit interleaved coded modulation
- system design in communications standards

Learning & Teaching

Learning & teaching methods

Activity	Description	Hours
Lecture		36
Tutorial		12

Assessment

Assessment methods

Method	Hours	Percentage contribution
Exam	2.5 hours	100%

Referral Method: By examination

Share this module Facebook Twitter Weibo

ELEC3202 Green Electronics

Module Overview

This module describes in detail recent development in electronic devices that reduce energy consumption, generate power, or advance the dsitribution of power. Together these set of devices will play an essential role in the reduced dependence on fossil fuels.

The module provides an introduction to both the fundamentals of energy generating electronic devices and the systems that can be implemented using such devices. The concepts will be explained in detail for photo-voltaic devices but the analogy for thermo-electric devices is evident. The module covers the fundamental theoretical foundations , manufacturing and practical limitations. System integration with the grid is also introduced with key concepts such as Smart Grids, Smart Meters, microgrids and storage being covered in the course.

Aims & Objectives

Aims

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

fundamental theory and principles of energy generating electronic devices
basic concepts of the interaction between chemical and electronic processes and in electrical energy storage devices

Subject Specific Intellectual

Having successfully completed this module, you will be able to:

understand manufacturing and efficiency issues in photovoltaic devices
understand key principles of power electronic circuits used in photovoltaic systemsystems

Subject Specific Practical

Having successfully completed this module, you will be able to:

simulate device and circuit operation of a photovoltaic system

Syllabus

Semiconductor Devices

Solar Cells (photovoltaics)
Thermo-Electric Materials
Light Emitting Diodes (LED)

Electrical Energy Storage

Batteries
Super Capacitors
Fuel Cells

Details of photovoltaic Devices & Systems

(Quantum) Efficiencies
Physical Models and Simulation
Device Manufacture Technologies
Photovoltaic System Design
Equivalent Circuit Models
Power Conversion techniques
Maximum Power Point Tracking
Grid Connection

Learning & Teaching

Learning & teaching methods

Activity	Description	Hours
Lecture		36
Computer Lab		6

Assessment

Assessment methods

Method	Hours	Percentage contribution
Photo-voltaic exercise	-	30%
Exam	2 hours	70%

Referral Method: By examination

Share this module Facebook Twitter Weibo

COMP3202 Knowledge, Information & Society

Module Overview

This module aim to critically explore the relationship between information technology and society and to prepare you to participate actively in ethical vocationally-related deployment of information technologies.

Aims & Objectives

Aims

Describe the relationship between information technology and society
Debate critically a variety of viewpoints surrounding technology and society
Demonstrate familiarity with key international issues such as privacy and information rights
Analyse the Professional’s role in the IT industry;

identify the key ethical and legal issues in Information Technology for Society
justify, and use a cohesive code of Professional Practice pertaining to information systems
describe legal concerns relevant to an IT Manager

Syllabus

Management Issues in IT : Contractual restraints; Compromises in systems planning; Constraints of a legal nature; Professional Issues in IT.

Professional societies: Career structures; Ethics; Codes of conduct and practice; Liability; Contractual obligations in software;

Legal Issues in IT: Copyright and patent; Trade secrets and registered design; Computer generated evidence; Obscene publications

The module will analyse technology dependency in social, organisational and global contexts through time. You will explore the relationship between information technology and technologies in general. You will also explore the uniqueness of information technology.

Case studies in key areas of current interest will be presented covering the broad themes of:

knowledge - technology's effect on the storage, transmission, recording and dissemination/communication of knowledge, digital news-media, distance learning and education, the knowledge economy;
information - definitions of information and data, relationships to people, data capture, storage and retrieval, biometrics and individual identity;
Society - global societal issues such as privacy rights, internet-related legislation, public and private knowledge and information, electronic/on-line voting and civil liberty.

The above examples are included for illustrative purposes and will vary from year to year. The unit will extrapolate the trends studied and speculate on the future of technology in everyday life and work.

Learning & Teaching

Learning & teaching methods

Activity	Description	Hours
Lecture	The lectures will cover the relationship between information technology and society. Students may use the Backboard discussion form to propose and answer each other questions.	36

Assessment

Assessment methods

Method	Hours	Percentage contribution
Coursework Assignment (1000 words) Descriptive annotated bibliography	-	15%
Coursework Assignment Essay (2500 words) plus draft plans and feedback on other students	-	80%
Coursework Assignment (500 words) feedback on other students work	-	5%

Referral Method: By set coursework assignment(s)

Share this module Facebook Twitter Weibo

COMP3201 Cyber Security

Module Overview

This module will teach the basic principles of security in IT systems and how these principles apply in a range of different contexts (e.g. computer systems, computer networks, network & system administration, eCommerce, etc.)

Aims & Objectives

Aims

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

A road map of security issues
The basic principles of security
Issues in Web-based security

Subject Specific Intellectual

Having successfully completed this module, you will be able to:

Explain how security principles apply in a range of contexts
Critically analyse Web based systems for security problems
Describe on-going trends in security threats and countermeasures

Subject Specific Practical

Having successfully completed this module, you will be able to:

Identify a range of alternative solutions to a security issue and select the most appropriate
Evaluate the outcome of the solution

Syllabus

Security and privacy – models of security.
Risk and Planning for Security
Social Engineering
Introduction to cryptography
Physical and logical security
Web based Security
e-Commerce, digital signatures and e-Banking

Learning & Teaching

Learning & teaching methods

Activity	Description	Hours
Lecture	The lecturers will present the theoretical and practical aspects of Cyber security.	36

Assessment

Assessment methods

Method	Hours	Percentage contribution
Coursework Assignment Identify faults in web based security	-	20%
Coursework Assignment Identify and fix faults in web based security	-	30%
Exam	2 hours	50%

Referral Method: By examination

Share this module Facebook Twitter Weibo

ELEC3201 Robotic Systems

Module Overview

Robots are becoming more widely used in society, with applications ranging from agriculture through to manufacturing, with increasing interest in autonomous systems.

This module will introduce students to the fundamentals of robotic systems including kinematics and dynamics as applied to manipulators and mobile robots. To support many application sensors are required, the module will discuss tactile and vision sensing as applied to both fixed and modile robots. The design and control of multifingered end effectors will be considered in detail. The module will conclude with a study on how biological systems have influenced the development of current and future robotic systems, including swarms and humanoid robotic systems.

Aims & Objectives

Aims

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

Be able to identify the limitations of a robot (either mobile or static), together with its end effectors and sensors, when applied to a specific environment or task.

Subject Specific Intellectual

Having successfully completed this module, you will be able to:

Analyse the kinematics of a robot and its associated control system.
escribe the operation and application of a range of sensors (e.g. vision, tactile) and how they can be applied to a mobile or static robot system
Appreciated the relevance of the biology-robotic interface and how it can benefit both the understanding of biological systems and the design of individual or groups of robots
Develop control algorithms for individual robots or robot swarms, to undertake simple tasks such as foraging.

Syllabus

Introduction: Definition of robotic systems, including an overview of manufacturing systems, biologically inspired robotics, medical applications, and space applications.

Manipulators: Classification of types of robot; identification of manipulator components and terminology; joints classification; mobile robot platforms.

Kinematics: Axis transformations as applied to robotics; application and definition of the DH matrix; forward and reverse kinematics; introduction to Jacobian and dynamic performance; path generation; definition of workspace.

Teleoperation: Master-slave systems; supervisory control; latency problems;

Robotic end effectors: Characteristic of the human hand; underactuated systems; stable grip; constraints; types of contact; mathematical representation of stable grip; use of screw twist, and wrench gripper design.

Tactile Sensors: Construction of tactile, and touch sensors; interpretation of sensory information; use of sensory data to determine kinematic information; peg into hole problem; contacts; RCC and IRCC systems.

Vision Systems: computer vision; sobal operator; perception; optical flow; road car and quad-copter navigation.

Biologically Inspired robotics: bio-inspired morphologies, sensors and actuators; what is intelligence; reactive and deliberative control; learning; SLAM; Behaviours; multi-robot and swarm systems.

Learning & Teaching

Learning & teaching methods

All students will be provided with a hard copy of the lectured material. A number of tutoral sessions will be provide, particularly to cover the kinematic and control aspects of the module.

Activity	Description	Hours
Lecture		36

Assessment

Assessment methods

Method	Hours	Percentage contribution
Kinematic design and analysis of robotic systems	-	25%
Exam	2 hours	75%

Referral Method: By examination, with the original coursework mark being carried forward

Share this module Facebook Twitter Weibo