digital technologies
IDEAS is a new multi-disciplinary research centre encompassing the disciplines of Engineering, Computing, Architecture & Built Environment and Art & Design.
It builds on acknowledged international research excellence, exploiting the rich potential of the interfaces between these diverse disciplines.
Our key research theme are: Creativity, Design & Innovation Digital Technologies Ideas Energy, Environment & Sustainability research institute Innovation, DEsign And Sustainability Centre for Video Communications
Our research and www.rgu.ac.uk/eng/cvc development work covers the technology of imaging Contact: Dr Sampath Kannangara, and communication. Dr Yafan Zhao Dr Laura Muir
Centre for Video Communications, School of Engineering The Robert Gordon University Schoolhill, Aberdeen Ideas AB10 1FR research Tel: +44 1224 262423 institute Innovation, DEsign And Sustainability Our active research areas include, image and video compression (coding), compression standards (MPEG1/2/4, H.264/AVC, SVC, RVC), video quality metrics and perceptually optimised video coding, low-complexity video coding, applied visual communications (including video compression for sign language communication) and transport of compressed multimedia data across networks.
CURRENT PROJECTS Fast video coding: estimation based control of video codec complexity Funded by EPSRC, this new approach delivers high quality compressed video whilst controlling rate and computation to match the resource availability of a power- or computation-constrained platform.
Transport of configurable video data for configurable video coding Re-configurable / Fully-configurable video coding is a radical new concept in video coding where a receiver is automatically configured to decode any video format. This project is to develop a novel framework for efficient and robust transport of configurable video data. This new framework will enable the adaptation of configurable video coding in a variety of industry applications such as television broadcasting and multimedia streaming over the internet.
Perceptually optimised rate control for video coding This project started in April 2010. Bit-rate control is an essential part of video compression and communication. State-of-the-art rate control schemes are only designed to minimise the objective video degradations based on error measurements. The aim of this project is to develop new rate control algorithms that maximise perceptual / visual video quality whilst satisfying bandwidth constraints.
Visual Quality Measurement for Broadcasting With the advent of HDTV broadcasting, there is significant industry interest in optimising compression techniques to maximise visual quality. The aim of this project is to develop a video quality measurement tool that can mimic specialist video quality evaluators or observers, so- called, “Golden eyes” that can measure small changes in visual quality by detecting artefacts that affects the visual experience.
VClear: Perceptually Optimised Video Compression This project developed from a Scottish Enterprise Proof of Concept award, it was awarded second place in the Thales Scottish Technology Prize 2009 and is currently being developed for commercial applications. The patented technology provides better video image quality at low bandwidths than standard video CODECs by giving priority in the coding scheme to perceptually important image content. It is currently available as a real-time software package which demonstrates the concept using “live” video captured from a camera and can be integrated into any system/ instrument that makes use of video coding, streaming and display.
www.rgu.ac.uk/ideas • [email protected] Information Retrieval
Information Retrieval (IR) is the www.comp.rgu.ac.uk/staff/ds/ study of methods and systems for representing, organising and retrieving information from online text and multimedia Contact: document collections and Professor Dawei Song data repositories to support T: 01224 262475 users’ information seeking and knowledge discovery. E: [email protected] Ideas research institute Innovation, DEsign And Sustainability Information Retrieval
Our research is focused on the following directions: - Text Document and Entity Retrieval - Multimedia and Social Information Retrieval - User Modelling and Interaction - Domain knowledge structure discovery and adaption
The AutoAdapt Project (funded by EPSRC: EP/F035705/1)
The goal of the project is to find ways of aiding the information seeking process within the intranets by providing: - A model of document collections that summarise the underlying knowledge structures, and to guide seekers to explore the information space. - A trail of information scent throughout the user’s search process and space. - The self-adaption of these to changing collections and users over time.
The Renaissance Project (Funded by EPSRC: EP/F014708/2)
The project aims to provide a unified framework and effective mechanisms to integrate context-sensitive and multimodal search, leading to a revolutionary shift of the Information Retrieval paradigm. Special attention is paid to verifying, quantifying, formalising and operating the “entanglements” between users, textual and multimedia content and retrieval contexts, i.e. how they are interacting with each other in an integrated way, to support more effective contextual IR systems.
Content-Based Image and Video Retrieval (Funded in part by Northern Research Partnership)
We are incorporating visual content, textual, ontological, and social information into retrieval systems. Current research is focused on extracting local features, building “visual words”, and applying these methods to adaptive user profiling in image retrieval. In video retrieval, we aim to consider not only “what it is”, but also “where it is” and “how it behaves” by utilising spatial and temporal features when modelling the content of videos. The motion patterns of visual words are recorded and classified to represent the spatial-temporal structures within a video.
www.rgu.ac.uk/ideas • [email protected] depict: DEVELOPING THE ICT BUSINESS BASE
www.comp.rgu.ac.uk/docs/is/
Contact:
Professor Patrik O’Brian Holt
Tel: +44 1224 262700 Ideas research institute Innovation, DEsign And Sustainability What is dePICT? dePICT (developing the ICT Business Base) is an RGU led initiative that aims to establish a new and innovate collaborative pooling network of academia and SMEs in the North East of Scotland, Highlands and Lowlands. The project is product driven and will, through new ways of working, deliver new and improved products with increased marketability, greater flexibility and routes to global exploitation. SMEs will be assisted in developing new products but also to move from a service orientation to a global product focus. The dePICT project will run from 2010 to 2012 and is funded by EU ERDF Priority 1 and the Scottish Government SEEKIT programme.
How does dePICT work? dePICT partners will work with SMEs through initial feasibility studies before providing assistance in obtaining external funding for new and novel R&D in a partnership between industry and academia. dePICT Partnership In the dePICT project innovation will be driven by the Joint Research Institute for Computational Systems (JRIcs), which is part of the Northern Research Partnership in Engineering (NRPe), a Scottish Funding Council funded pooling. The JRIcs pools expertise from three universities, the Robert Gordon University, Dundee University and the University of Aberdeen. The academic partners represent recognized international excellence in research and will provide expertise and experience in research and research project management. dePICT has support from Scottish Enterprise, Interface, KTP, TSB and other economic development agencies, Scotland IS as well as various SMEs.
Impact of dePICT The primary aim of dePICT is to assist SMEs to enhance and develop new ICT products through increased research and development. An important aspect of the project is the expansion and diversification of skills and expertise. There will be a focus initially on ICT related SMEs that work in the Oil, Gas and Energy sectors, but will also include companies and organisations outside these sectors. This will allow SMEs to expand into new sectors and to exploit global markets.
In addition to new and improved products, job creation and the expansion of markets, the project aims to introduce and sustain innovative collaborative methods of working that will build permanent bridges between SMEs and academia to mutual benefit. These activities will contribute to enhancing ICT skills in the SME sector. This mirrors other activities currently seen in Oil and Gas where large organisations are establishing new and novel collaborations using the Northern Research Partnership in Engineering as a core facilitator as well as a source of recognised expertise.
www.rgu.ac.uk/ideas • [email protected] CoNSTRAINTS Research Group
www.comp.rgu.ac.uk/docs/kbs/constraintsGroup
Solving and optimisation Contact: Dr Hatem Ahriz of problems which may be Dr Inés Arana distributed and/or dynamic email: [email protected] Tel: +44 1224 262716 Ideas research institute Innovation, DEsign And Sustainability The IDEAS Constraints research group focuses on the research and development of techniques for solving and optimising the solution of complex combinatorial problems that can be represented by a set of variables and a set of constraints that restrict the values which variables can take simultaneously. Constraint technologies are used to find (optimal) solutions to a wide range of challenging industrial problems including meeting scheduling, resource allocation, engineering re-design and timetabling.
RESEARCH OVERVIEW The group develops techniques for finding (optimal) solutions to constraint problems. The following areas are investigated: • Distributed vs. Centralised problems • Static vs. Dynamic problems • Solutions vs. Optimal solutions and best Compromises • Single vs. Hybrid techniques.
Distributed Constraint Satisfaction Distributed Constraint Satisfaction Problems (DisCSPs) is an emerging area of constraint programming where the problem is naturally distributed amongst several locations and cannot be solved in a centralised manner due to resource, privacy and/or security issues. Thus, the problem consists of a set of related sub-problems, each of which is solved by a software agent. Agents communicate with each other in order to ensure that their sub-solutions are compatible so that sub-solutions can be combined in order to obtain a global solution. The fast-growing use of the internet, intranet and virtual organisations and the ever-increasing amount of information accessible through them has brought a demand for more sophisticated constraint satisfaction services which can help exploit these information resources. We develop efficient algorithms for solving DisCSPs in both static and dynamic environments.
Dynamic Constraint Satisfaction Dynamic constraint satisfaction solves problems where the specification changes over time, i.e. new constraints and/or variables are added/deleted. We investigate dynamic constraints in distributed environments and we develop algorithms for solving problems where constraints change over time.
We have developed several constructive algorithms for dynamic constraint satisfaction. These algorithms handle problem changes by modifying the existing solution while raising the knowledge gained from solving the original problem. Empirical results suggest faster problem resolution and increased stability.
Optimisation – best solutions and best compromises Optimisation techniques find solutions which satisfy all constraints while optimising an objective function. This can be used not only to find the best solutions to problems, but also to find the best compromise where the problem is over- constrained and, therefore, no solution which satisfies all constraints can be found. We have developed efficient optimisation algorithms for over-constrained problems.
Hybrid algorithms – finding solutions quickly with guarantees Constraint problems can be solved by: (i) Systematic search algorithms, which are complete, but can take exponential time; (ii) Local search algorithms, which are incomplete, but faster for the resolution of large problems. We develop hybrid algorithms which combine the knowledge learnt on incomplete local searches in order to assist systematic search algorithms. Our algorithms use local search to learn about areas of the problem which are particularly challenging to satisfy and promising variable instantiations. This knowledge is used by systematic search algorithms to find solutions faster.
www.rgu.ac.uk/ideas • [email protected] Computational Intelligence
Learn, Optimise, C ompute!
The IDEAS Computational www.comp.rgu.ac.uk/research/cig Intelligence research group has a primary focus in three Andrei Petrovski related areas: evolutionary John McCall algorithms; probabilistic Horacio Gonzalez-Velez modelling; and parallel Contact: computing. Andrei Petrovski E: [email protected] Ideas Tel: +44 1224 26270 research institute Innovation, DEsign And Sustainability Learn, Optimise, Compute!
We specialise in adaptive, intelligent computational approaches to problem-solving. Many real-world problems are complex, involving the consideration of vast amounts of data, the balancing of multiple objectives within challenging constraints and the evolving requirements for information and communication resources. We research powerful computational approaches to discover key relationships in data, to intelligently search for solutions in complex scenarios and to provide high performance computing strategies that best adapt resources to demands.
Research Application Areas • prediction of pathological staging in prostate cancer • chemotherapy treatment design and optimisation • care visit scheduling • data modelling for rig operations • concurrent mining of neuro-oncological data • parallel molecular dynamics of nano-materials
Technical Interests • Data modelling and inference using probabilistic graphical models such as Bayesian and Markov network models. • Theory and applications of a wide range of naturally inspired techniques for single- and multi-objective optimisation, including evolutionary algorithms, particle swarms, ant colonies and • estimation of distribution algorithms. • Models and applications of computational science and parallel systems, including structured parallelism, algorithmic skeletons and parallel patterns, cloud and grid computing, heuristic scheduling, and resource adaptivity.
Collaboration and funding
The group has strong collaborative links with other institutions worldwide. We are members of the world-leading Scottish Informatics and Computer Science Alliance (SICSA) with strong representation in the Complex Systems Engineering theme. We also belong to the Northern Research Partnership, where we have strong links to the Medical Technologies JRI. Collaborators include: British Telecom plc, GlaxoSmithKline plc, NHS Grampian, the DTI, ODS-Petrodata Ltd., and Technology Managers Ltd. Funding is received from: EPSRC, SHEFC, TSB (KTP), NESTA, The European Commission, NHS, Scottish Enterprise, The Carnegie Trust, The Nuffield Foundation; industrial consultancy and charities.
www.rgu.ac.uk/ideas • [email protected] Cognitive Engineering Research Group
Cognitive Engineering involves a www.comp.rgu.ac.uk/docs/is/ multidisciplinary approach to the analysis, design, implementation and evaluation of highly complex Contact: interactive systems. Professor Patrik O’Brian Holt
Tel: +44 1224 262700 Ideas research institute Innovation, DEsign And Sustainability The academic aims are to understand human interaction with complex systems while the applied objectives are to design and build novel interactive systems that are highly usable.
Cognitive Engineering at RGU
Cognitive Engineering research at RGU focuses on imaging, graphics, visualisation, cognitive & performance modelling and complex visual user interaction. All the research has a common theme of visualisation and visual interaction and this is manifested in a number of themes: • Optimisation of graphical user interface layouts with cognitive modelling and genetic algorithms. • Face recognition and facial modelling. • Perceptual and cognitive issues in visual interaction and communication. • Visual Learning Systems. • Human error modelling in visual communications. • Wearable and portable Augmented and Virtual Reality Systems. • Visualising complex statistical data. Additionally, we do applied work in Usability Engineering, Usability Evaluation and User Experience data capture.
Application Areas
Our research is applied in a number of different areas that include: • Medicine (Telemedicine & Human Error Modelling; Data Visualisation; Facial Modelling). • Oil and Gas (Human Error Modelling; Usability Engineering; Data Visualisation). • Aerospace (Augmented Wearable Virtual Reality; Usability Engineering; Visual Learning). • Games (Face recognition and Facial Modelling). • Trauma Therapy (Augmented Virtual Reality).
Industrial Links
We lead the dePICT project (Developing the ICT Business Base) which aims to support SMEs in the North East to develop and globalise advanced ICT products. The project has a value of £1.1M with funding from EU ERDF Priority 1 and the Scottish Government SEEKIT programme. Members of the group have acted as consultants for numerous organisations such as NHS (Scotland), Scottish Government, Lockheed-Martin Avionics, BAE SYSTEMS, Selex Galileo, ConocoPhillips.
Partnerships
The Cognitive Engineering Research Group leads the Joint Research Institute for Computational Systems, which is part of the Northern Research Partnership in Engineering, a pooling initiative funded by the Scottish Funding Council. We work in partnership with Dundee University and the University of Aberdeen. We are also members of the world-leading Scottish Informatics and Computer Science Alliance (SICSA).
www.rgu.ac.uk/ideas • [email protected] Case Based Reasoning: Reusing Experiences
Closing the Loop www.comp.rgu.ac.uk/docs/kbs/ between Corporate Professor Susam Craw Knowledge Dr Nirmalie Wiratunga and Dr Rob Lothian Dr Stewart Massie Innovation Contact: Dr Nirmalie Wiratunga Ideas E: [email protected] research T: +44 1224 262573 institute Innovation, DEsign And Sustainability Corporate Collaborators: European Space Agency, AxSys Technology Ltd, XCD Ltd, NHS Grampian, British Geological Survey, AstraZeneca
Academic Collaborators: Aberdeen University, Dundee University, Universidad Complutense de Madrid, Université Laval, Indian Institute of Technology Madras
Research Overview Case Based Reasoning (CBR) solves problems by retrieving and reusing similar experiences that are stored in a case base of previously solved problems and their solutions. This research has developed innovative techniques for building and applying case-based systems for real-world problems, especially decision support, product design, project planning and information management.
Reasoning from Experiences Case-based decision support systems have been developed for various problem domains: evidence-based decision making in healthcare from Excelicare electronic patient record data, project planning for well engineering in the Oil & Gas industry, and a joint project with AstraZeneca designing pharmaceutical formulations.
Research has developed knowledge-light learning techniques that use only the cases in the case-base to learn explicit knowledge to improve the design and maintenance of CBR systems. Case knowledge is at the heart of a CBR system. A novel complexity-based competence model is the basis of editing tools that have been effective in discovering new cases, reducing redundancy and removing faulty cases.
Effective similarity-based retrieval is essential for CBR, and adaptation of the retrieved solution is often necessary for case-based design and planning. A software tool has been developed that transforms a database of solved cases into a fully-fledged case-based system. Applied to tablet design for AstraZeneca, this research successfully replicated knowledge engineering results that were expensive to achieve manually.
Knowledge Discovery from Text Textual CBR has been applied in various domains where experiences are predominantly captured in text form: a joint project with ESA for reusing satellite anomaly reports; email workflow management for the ageing population; designing supported home-living solutions from occupational therapists’ reports; health and safety report management for Grampian NHS; and text generation for weather forecasting. More recent projects address multimedia data for image management and music recommendation.
A suite of text mining software components has been developed to extend the open-source jCOLIBRI CBR framework. Concept discovery algorithms establish similar context within textual content. Semantic knowledge is extracted from concepts and organised into domain-specific taxonomies. Layered architectures integrate existing natural language processing tools with information extraction and natural language processing functionality. Finally a template based GUI guides the design of TCBR systems followed by Java code generation by jCOLIBRI. The generic nature of these software components allows easy integration with large- scale text collections and industrial databases.
www.rgu.ac.uk/ideas • [email protected]