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Electronics and Computer Science

COMP6221 Computational Thinking

Module Overview

The aim of this module is to provide non-computer science specialists (especially those who do not have any experience of programming) with an understanding of the topics, issues and challenges in Computer Science that will enable them to engage computational approaches to problems while acting as professionals and researchers in related fields. This principles of this module are based on Wing, J. (2006) Computational thinking, Communications of the ACM, v.49 n.3.

The discipline of Computer Science is built on a broad understanding of hardware systems, software algorithms, computation, information handling, modelling; topics that are laid out in the standard ACM Computer Science curriculum. A Bachelors degree introduces students to these areas and attempts to give expertise in a range of these subjects (the choice of which is determined by the focus of the course). A Masters level Computing degree will provide a more intensive treatment of these topics, with an aim to allow the student to work at the forefront of the discipline. This module aims to provide students who do not have a computing background with an understanding of the scope and importance of the broad range of computer science topics.

Aims & Objectives

Aims

After completing this course you will
  • the nature and history of Computer Science as an emerging research area
  • the breadth of Computer Science discipline
  • develop understanding of key areas of Computer Science
  • gain familiarity with topical isues in Computer Science (e.g. Internet of Things, 3D printing)
  • have experience in simple programming techniques
  • design and create an animated toy or household object using a Raspberry Pi
After successfully completing this course you will be able to
  • communicate technical concepts to a lay audience, in live opresentations and online, written material
  • develop and deliver outreach material in teams
  • create educational material for a school curriculum
 

Syllabus

  • Operating systems (1960s, resource management, UNIX/Linux, Windows, Mac, thin clients, cloud computing)
  • Databases (SQL, third normal form, Hadoop, data centres)
  • Devices (Mainframes, PCs, iPhones, sensor networks)
  • Programming Languages (binary, assembler, C, Object orientation, Java, LISP, Prolog, functional, scripting)
  • Algorithms (sorting, complexity, tractability, IP)
  • Artificial Intelligence (Lisa to Machine Learning, Neural Networks)
  • Graphics (OpenGL, PS3! GPUs)
  • Software Engineering (methodologies, projects, mythical man year)
  • Networks (Ethernet, X25, TCP/IP, routers, IPv6, Wifi, 3G, Wimax).
  • Python Programming
  • Raspberry Pi

Learning & Teaching

Learning & teaching methods

ActivityDescriptionHours
LectureComputing Science principles and techniques8
Computer LabHands on Python & Raspberry Pi sessions10

Assessment

Assessment methods

MethodHoursPercentage contribution
Public Engagement Presentations-40%
Teaching Activity-20%
Programming Labs-20%
Raspberry Pi Coursework-20%

Referral Method: By set coursework assignment(s)

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ELEC6230 VLSI Systems Design

Module Overview

To provide an understanding of the design and layout of digital VLSI circuits and systems through laboratories and design exercises making use of appropriate CAD tools.

Aims & Objectives

Aims

Knowledge and Understanding

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

  • The design of digital CMOS integrated circuit cells
  • The design of small digital systems using predfined cells
  • The use of CAD tools in the design process

Subject Specific Intellectual

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

  • Understand the principles of digital CMOS integrated circuit design
  • Derive compact and efficient circuit structures to implement digital functions

Transferable and Generic

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

  • Perform basic tasks on a Unix workstation
  • Organise your work in a logical manner in a Unix filesystem
  • Collaborate with others to agree a common specification and share out work
  • Communicate your work accurately and concisely through written reports

Subject Specific Practical

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

  • Design digital CMOS cells using a layout editor
  • Verify the functionality and performance of CMOS designs using simulation tools
  • Design digital systems using hardware description language
  • Assemble CMOS cells to implement digital systems using a layout editor
  • Design test benches to verify digital systems using hardware description language

Syllabus

  • Layout for VLSI
    • Cell layout
    • Standard cell layout
    • Full and semi-custom design
    • Floorplanning
    • Bit slice design
  • Digital design using SystemVerilog
    • Introduction to SystemVerilog
    • Design for Synthesis
  • CAD Tools & Techniques
    • Magic VLSI layout editor
    • HSpice analogue circuit simulator
    • SystemVerilog Hardware Description Language and digital simulator
    • Cadence IC design toolset

Learning & Teaching

Learning & teaching methods

ActivityDescriptionHours
Computer LabA three-hour laboratory slot is reserved once per week to assist students.36
LectureLectures to support the laboratory activities and to prepare for second semester VLSI design.24

Assessment

Assessment methods

MethodHoursPercentage contribution
Mini design assignment with electronic submission of designs - Desex1-10%
Mini design assignment with electronic submission of designs - Desex2-20%
Design assignment with formal documentation - Desex3-35%
Design assignment with formal documentation - Desex4-35%
Lab (attendance and log book assessment)-25%
Calculation of final mark = (Desex1 + Desex2 + Desex3 + Desex4) * ( 75% + LABmark )-100%

Referral Method: By set coursework assignment(s)

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ELEC6225 High Voltage Insulation Systems

Module Overview

This module provides a systematic understanding of knowledge and critical awareness of issues related to the management and design of high voltage insulation systems. The course introduces a number of topics related to the design and testing of insulation systems and breakdown phenomena in insulation materials. The students will also be exposed to research activities undertaken within the Tony Davies High Voltage Laboratory. The lectures (seminars) are intended to support student self-learning activities and it is expected that the students should make use of a wide range of information resources including current IEC standards and research papers. Two assessment activities are designed to provide scope for students to work as a team (bushing insulation design) and individually (partial discharge classification). A range of skills, including technical (electric field simulation and programming) and transferable skills (presentation) are required to complete the two assignments.   

 

Students are not required to have taken ELEC3211 before taking ELEC6225, but it is strongly recommended.

Aims & Objectives

Aims

Knowledge and Understanding

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

  • exposure to a range of insulation materials and composites used in HV insulation systems and their electrical properties
  • different requirements and compromised decision in practice when selecting insulation materials
  • communication and presentation skills

Subject Specific Intellectual

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

  • learn a comprehensive range of testing and measurement techniques to characterise insulation materials
  • acquire knowledge of electric field modelling and electric field control
  • acquire knowledge of partial discharges, condition monitoring and insulation quality assessment
  • expose to frontier research activities in high voltage insulation

Subject Specific Practical

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

  • design insulation system according to IEC standards

Syllabus

Insulation System Design, Electrical Breakdown and Materials (8 Lectures)

Review of electrical insulating materials, properties, composites, use in HV equipment, partial discharges, material ageing, surface and bulk breakdown processes. Cable, transformer, capacitors and Bushing Insulation design and stress control.

HV Testing and Measurement Techniques (6 Lectures)

International, BSI and IEEE Standards. Partial discharge, capacitance tan delta, withstand, lightening impulse etc. Material based of current IEC standards. Condition monitoring and assessment of HV insulation systems.

Research Issues (6 lectures)

Solid Insulation: Electrical treeing and short-term breakdown processes, test geometries, environmental factors. Short term breakdown tests. Condition assessment, partial discharge detection and characterisation.

Liquid Insulation: Discharges in oil, DGA and degradation of transformer oil.

Gas Insulation: Production of corona, plasma, problems and applications

Electrical Field Control and Insulation Design (4 lectures)

Bushing design

Cable insulation design

Learning & Teaching

Learning & teaching methods

ActivityDescriptionHours
LectureLectures covering core materials24
TutorialAssignment One progress meeting and feedback sessions for CWs 4

Assessment

Assessment methods

MethodHoursPercentage contribution
275 kV Bushing Insulation Design - Students work in groups to design 275 kV bushing based on materials and dimensions provided using one of the two electric field grading methods. The electric field at crucial regions needs to be simulated using available software. Assessment based on the electric field, PD inception voltage and flashover voltage should be made on the bushing. -60%
Partial discharges and clsssifcation - In this work the students work in paris. They are required to do 10 minutes oral presentation on PD and PD classification/identification. They are also required to write a program that can identify PD type from an unknown data obtained from HV laboratory.-40%

Referral Method: By set coursework assignment(s)

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ELEC2219 Electromagnetism for EEE

Module Overview

This module introduces and develops the knowledge in fundamental electromagnetics for second year Electrical and Electronic Engineering students. The course presents the basic concepts of electromagnetic theory from a physical and application point of view. The vector algebra used in electromagnetic theory is introduced in the electromagnetic field context. The course uses numerical methods to solve and visualise electromagnetic fields for simple problems so that students gain a better understanding of the electromagnetic field theory which is core of any electrical and electronic engineering degree.

The students should have covered in their first year Mathematics for Electronic and Electrical Engineering (MATH 1055) and Electric Materials and Fields course (ELEC 1206). Although these two courses are not pre-requisites, students will cope better with the material of this course if MATH 1055 and ELEC 1206 were already covered in their first year.

Aims & Objectives

Aims

Knowledge and Understanding

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

  • Basic concepts of electromagnetic theory
  • Vector algebra in the electromagnetic field context
  • Properties of static and time-varying electromagnetic fields
  • Physical meaning of Maxwell's equations
  • Mathematical description of fundamental laws of electromagnetism
  • Electric and magnetic properties of matter
  • Principles of electromagnetic radiation
  • Fundamentals of modelling and simulation techniques applied to electromagnetics
  • Principles of finite difference and finite element formulations
  • Advantages and limitations of various field modelling techniques

Subject Specific Intellectual

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

  • Appreciate the role of computational electromagnetics in engineering
  • Identify different types of equations governing electromagnetic processes
  • Derive equations describing electromagnetic phenomena
  • Formulate fundamental laws of electromagnetism
  • Solve differential equations using separation of variables
  • Analyse simple electromagnetic systems
  • Appreciate the complexity of CAD systems for electromagnetic design
  • Distinguish between various stages associated with CAD
  • Design models suitable to analyse performance of electromagnetic devices
  • Relate field displays to fundamental concepts of electromagnetics

Transferable and Generic

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

  • Write programs using C language and Matlab scripts
  • Use electromagnetic CAD packages
  • Write technical reports
  • Work in a small team to conduct an experiment

Subject Specific Practical

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

  • Demonstrate electromagnetic theory applied to simple practical situations
  • Explain the meaning and consequences of field theory
  • Apply Maxwell's equations to problems involving simple configurations
  • Interpret electromagnetic solutions
  • Explain the operation of simple electromagnetic devices
  • Apply mathematical methods and vector algebra to practical problems
  • Be familiar with running commercial finite element software for electromagnetics
  • Set up, solve and interrogate solutions to problems using FE software

Syllabus

  1. Approximate methods of field solution - Geometrical properties of fields; method of 'tubes and slices'.
  2. Flow of steady current - Potential gradient; current density; geometrical properties of fields; divergence; nabla operator; Laplace's equation.
  3. Electrostatics - The electric field vector; scalar electric potential; Gauss's theorem and divergence; conservative fields; Laplace and Poisson equations; electric dipole, line charge, surface charge; solution of Laplace's equation by separation of variables; polarisation; dielectrics, electric boundary conditions.
  4. Magnetostatics  - Non-conservative fields, Ampere's law and curl; magnetic vector potential; magnetization and magnetic boundary conditions
  5. Electromagnetic induction - Faraday's law; induced and conservative components of the electric field, emf and potential difference.
  6. Maxwell's equations  - Displacement current; Maxwell's and constituent equations; the Lorentz guage; wave equation.
  7. Time-varying fields in conductors - Diffusion and Helmholtz equations; skin depth, surface impedance; eddy currents in slabs, plates andcylindrical conductors.
  8. Electromagnetic radiation - Current element; radiation resistance; plane waves; linear antenna; waveguides; reflection and refraction of light; total internal reflection in optical waveguides, and fibers.
  9. Principles of electromechanical energy conversion - Generalised variables for electromechanical systems; Hamilton’s principle and Lagrangian state function; conservative and non-conservative systems; examples.
  10. Computational aspects of approximate methods of field solution - The method of tubes and slices.
  11. Review of field equations - Classification of fields: Laplace's, Poisson's, Helmholtz, diffusion, wave equations; Vector and scalar formulations.
  12. Finite difference method - Five-point scheme, SOR; example; Diffusion and wave equations, explicit formulation, Crank-Nicholson implicit scheme, a weighted average approximation, alternating-direction implicit method; Convergence and stability; handling of boundary conditions; Alternative formulation of the finite-difference method.
  13. Finite element method - Variational formulation, first-order triangular elements, discretisation and matrix assembly; the art of sparse matrices; alternative approximate formulations (including Galerkin).

Learning & Teaching

Learning & teaching methods

ActivityDescriptionHours
Lecture36
Tutorial6
Specialist Lab9

Assessment

Assessment methods

MethodHoursPercentage contribution
Eddy current screening-5%
Magnetostatic screening – properties of magnetic materials (magnetic permeability)-5%
Radiation experiment – dipole and monopole radiation, differential transmission line, reflectors, directivity and radiation pattern-5%
TAS+FD+FE-17.5%
FE using Magnet-17.5%
Exam2 hours hours50%

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

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ELEC6218 Signal Processing

Module Overview

This module aims to introduce to the students signal processing techniques, including analogue and digital filter design and systems design theories. The module also introduces the concepts of statistical signal processing including estimation and detection theories, with illustrative case studies to demonstrate how these techniques can be used in communications systems.

Aims & Objectives

Aims

Knowledge and Understanding

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

  • Analyse the effect of sampling on electronics signals
  • Characterise random signals and processes
  • Apply statistical signal processing estimation techniques to communications systems

Subject Specific Practical

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

  • Design analogue and digital filters according to set specifications
  • Design adaptive filters

Syllabus

  • Analog filter design --- specifications, physical approximations, performance specifications, design. Covering Butterworth, Chebyshev, Elliptic types and their relative performance.
  • Sampling and reconstruction theory --- review of the basics
  • z transform analysis
  • Digital filter design ---- specifications, physical approximations, performance specifications, design. Covering Butterworth, Chebyshev, Elliptic types and their relative performance.
  • Random processes: models and processing
  • Adaptive filter design and implementation
  • Estimation Theory: Maximum Likelihood Estimation, Least squares estimation, Baysian estimation

Learning & Teaching

Learning & teaching methods

ActivityDescriptionHours
LectureThree lectures per week36
TutorialOne tutorial session per week12

Assessment

Assessment methods

MethodHoursPercentage contribution
Deterministic filter design coursework-10%
Statistical signal processing coursework-10%
Exam2 hours80%

Referral Method: By examination

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COMP6223 Computer Vision (MSc)

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.

This module will be taught together with COMP3204 Computer Vision. This module will have higher requirements on the desired learning outcomes which will be assessed by a different set of coursework. 

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:

  • Demonstrate awareness of the current key research issues in computer vision
  • 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

ActivityDescriptionHours
LectureLectures and demonstrations of material24
TutorialStudents develop and present implementations of basic material12

Assessment

Assessment methods

MethodHoursPercentage contribution
Experiment with a classical computer vision technique-10%
Build basic technique-15%
Group coursework -20%
Exam2 hours55%

Referral Method: By examination and a new coursework assignment

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COMP6220 Qualitative Research Methods for Assessing Technology

Module Overview

This module is a 5-credit (2.5 ECTS) augmentation of the 10 credit (5 ECTS) RESM6004 (Quantitative Research Methods) and provides the perspective of running a research project as a context for the consideration of research methods and research questions.

This module gives students the experience of developing a project proosal, selecting appropriate research methods and processes to adress a particular research question expressed as a compelling bid document.

Aims & Objectives

Aims

After successfully completing this course you will be able to

  • plan a programme of research, using approporiate resources and constrained by available budgets and timescale
  • clearly communicate your research rationale and plan in a proposal document

Syllabus

  • project planning
  • project budgets
  • ethical approval process
  • time management, GANT charts

Learning & Teaching

Learning & teaching methods

ActivityDescriptionHours
Lecture10

Assessment

Assessment methods

MethodHoursPercentage contribution
Group Research Project Bid-100%

Referral Method: By set coursework assignment(s)

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COMP6219 Designing Usable and Accessible Technologies

Module Overview

To explore the relationship between accessibility, usability and user experienceTo understand the role of Assistive technologies in achieving universal designTo prepare students to engage in research and development in accessibility, usability and user experience

Aims & Objectives

Aims

Knowledge and Understanding

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

  • Definitions of Usability and User Experience
  • Models of disability
  • Definitions of Assistive Technology and Universal Design
  • The interdisciplinary approach to design, research, evaluation
  • Assessment for assistive technology and universal design
  • Current research in assistive technology and universal design

Syllabus

  • Usability and User Experience
  • Case for universal design (Business, Legislation, Moral, self interest)
  • Models of disability
  • Ethical research issues
  • Assistive Technologies and Universal Design
  • Accessibility and Usability Standards
  • Assistive Technology Assessment and Evaluation
  • Involving users in research design and evaluation
  • Research in assistive technologies and universal design

Learning & Teaching

Learning & teaching methods

ActivityDescriptionHours
Lecture24
TutorialSeminar/workshop12

Assessment

Assessment methods

MethodHoursPercentage contribution
Written Report-70%
Web Site-20%
Oral Presentation-10%

Referral Method: By set coursework assignment(s)

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COMP6218 Web Architecture

Module Overview

In the second decade of the 21st century, the Web is so familiar to us that we have to be reminded that browsing had to be invented and there was a time when the extent of your digital information was confined to the resources that you could obtain on a CD-ROM drive. This module looks at the architecture underlying the Web, the hypertext research that has informed its development and the search engines and Web 2.0 applications that have made it more useful.

Aims & Objectives

Aims

Knowledge and Understanding

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

  • The technical architecture of the World Wide Web
  • Principles of Web information design
  • The common standards for identification, representation and interaction on the Web
  • The history of hypertext, its relationship with the Web, and current research issues

Subject Specific Intellectual

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

  • Identify the key characteristics of the Web Architecture
  • Apply the Representational State Transfer (REST) architectural style to Web application design
  • Critically evaluate developments on the Web

Subject Specific Practical

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

  • Use common Web technologies
  • Design RESTful Web applications

Syllabus

  • The Architecture of the World Wide Web
  • Hypertext: fundamentals, pioneers, writing, open hypermedia
  • Representational State Transfer
  • Markup Languages: XML, HTML, SVG, MathML, DOM
  • Protocols: HTTP, SOAP
  • Styling: CSS, XSLT
  • Data and Metadata: RSS, Atom, RDF
  • The Web graph
  • Applications: search engines, advertising, open access, open data

Learning & Teaching

Learning & teaching methods

ActivityDescriptionHours
Lecture36

Assessment

Assessment methods

MethodHoursPercentage contribution
Web Application Exercise-25%
Technical Report-25%
Exam2 hours50%

Referral Method: By examination

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COMP6217 The Science of Online Social Networks

Module Overview

Aims

  • To develop methods and techniques that employ a range of technologies for social networking
  • To understand how to measure the performance and behaviours of social networks
  • To understand the impact of social networks on different domains
  • To understand the challenges and affordances of social networking for society

Aims & Objectives

Aims

Knowledge and Understanding

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

  • Methodologies for social network analysis
  • Ways in which social network can influence developments in domains such as e-learning, enterprise and media
  • Critical considerations of societal requirements such as digital literacy, privacy, influence and trust

Intellectual Skills

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

  • Establish the potential of social networking technologies in specific contexts and domains
  • Articulate appropriate frameworks for the analysis of particular social networks
  • Communicate current societal challenges and anticipate emerging challenges

Subject-Specific Skills

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

  • Design appropriate social network solutions and interface or extend the designs of existing social network infrastructures
  • Identify and analyse social network characteristics
  • Identify and interpret domain and societal requirements for the deployment of social network solutions

Employability/Transferable/Key Skills

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

  • Work in a software design team
  • Evaluate existing software systems and infrastructures
  • Present a technological solution within a broader context

Syllabus

The topics covered will reflect the latest research and development activities in social networking. Including:

  • History of Social Networking Technologies and the Web
  • Digital Literacy and Web 2.0 systems
  • Online social networks and business
  • Graph theory and social networks
  • Game theory and social networks
  • Network dynamics
  • Linked Data and the Social Semantic Web (FOAF, SKOS, etc)
  • Privacy and identity in online social networks
  • Power and influence in online social networks
  • Trust in online social networks

Learning & Teaching

Learning & teaching methods

ActivityDescriptionHours
Lecture36

Assessment

Assessment methods

This module will be assessed 60% by exam and 40% by coursework that will include a significant group project element.

Students will be required to design and present a social networking application, system or tool; students will:

  • Prepare of portfolio of design materials
  • Take into account requirements for a specific context or domain
  • Explain the broader social, economic and legal impact of their solution

 Students will work in small groups to develop new applications or extend existing infrastructures and they will produce a portfolio of design evidence to accompany their software prototype. Subsequently, they will be required to pitch this portfolio in a presentation to a panel of experts from a range of different disciplines such as sociology, law, computer science and economics.

Coursework marking scheme (out of 100, worth 40%):

  • Portfolio of design materials – 60%
  • Dragon’s Den Presentation – 20%
  • Personal Reflection – 20%
MethodHoursPercentage contribution
Group Project-40%
Exam2 hours60%

Referral Method: By examination

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