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Data-driven Decision Support

Summary of the impact

Many organisations rely on increasingly large and complex datasets to inform operational decision- making. To assist decision-makers when decisions are data-driven, computational tools are needed that present reliable summary information and suggest options allied to the key objectives of decision-making. Research at RGU has developed novel learning and optimisation algorithms driven by multifactorial data and implemented this in commercial decision-support software. The research has had economic impact by providing products to be sold: drilling rig selection tool (ODS-Petrodata Ltd.) and subsea hydraulics diagnostic tool (Viper Subsea Ltd.). Further economic impact comes from operations management software developed for British Telecom.

Submitting Institution

Robert Gordon University

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Technological

Research Subject Area(s)

Mathematical Sciences: Numerical and Computational Mathematics, Statistics
Information and Computing Sciences: Artificial Intelligence and Image Processing

2. Meeting the Challenges of Data Security

Summary of the impact

The security of data in printing and network environments is an area of increasing concern to individuals, businesses, government organisations and security agencies throughout the world. Mathematical algorithms developed at the School of Mathematics at Cardiff University represent a significant step-change in existing data security techniques. The algorithms enable greater security in automatic document classification and summarisation, information retrieval and image understanding. Hewlett-Packard (HP), the world's leading PC vendor, funded the research underpinning this development and patented the resulting software, with the aim of strengthening its position as the market leader in this sector of the global information technology industry. Hewlett Packard has incorporated the algorithms in a schedule of upgrades to improve the key security features in over ten million of their electronic devices. Accordingly, the impact claimed is mitigating data security risks for HP users and clients and substantial economic gain for the company.

Submitting Institution

Cardiff University

Unit of Assessment

Mathematical Sciences

Summary Impact Type

Technological

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing
Medical and Health Sciences: Neurosciences

Impact of Machine-Learning based Visual Analytics

Summary of the impact

Visual analytics is a powerful method for understanding large and complex datasets that makes information accessible to non-statistically trained users. The Non-linearity and Complexity Research Group (NCRG) developed several fundamental algorithms and brought them to users by developing interactive software tools (e.g. Netlab pattern analysis toolbox in 2002 (more than 40,000 downloads), Data Visualisation and Modelling System (DVMS) in 2012).

Industrial products. These software tools are used by industrial partners (Pfizer, Dstl) in their business activities. The algorithms have been integrated into a commercial tool (p:IGI) used in geochemical analysis for oil and gas exploration with a 60% share of the worldwide market.

Improving business performance. As an enabling technology, visual analytics has played an important role in the data analysis that has led to the development of new products, such as the Body Volume Index, and the enhancement of existing products (Wheelright: automated vehicle tyre pressure measurement).

Impact on practitioners. The software is used to educate and train skilled people internationally in more than 6 different institutions and is also used by finance professionals.

Submitting Institution

Aston University

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Technological

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing, Computation Theory and Mathematics, Information Systems

SpendInsight

Summary of the impact

Bishop and Danicic contributed to the development of novel spend analysis software. Launched in 2011 as a commercial service by KTP industrial partners @UK PLC, SpendInsight has been used by over 380 organisations, including Basingstoke and North Hampshire NHS Foundation Trust, which, alone, cut procurement spend by £300,000 via savings identified using SpendInsight. An analysis produced by SpendInsight for the National Audit Office identified gross inefficiencies in NHS procurement, yielding potential annual overall savings of at least £500 million. The findings of this report were discussed in parliament and changes to NHS purchasing policy were recommended as a result.

Submitting Institution

Goldsmiths' College

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Economic

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing, Data Format, Information Systems

Data maps with applications to medical diagnostics and monitoring

Summary of the impact

Advanced technologies for data visualisation and data mining, developed in the Unit in collaboration with national and international teams, are widely applied for development of medical services. In particular, a system for canine lymphoma diagnosis and monitoring developed with [text removed for publication] has now been successfully tested using clinical data from several veterinary clinics. The risk maps produced by our technology provide early diagnosis of lymphoma several weeks before the clinical symptoms develop. [text removed for publication] has estimated the treatment test, named [text removed for publication], developed with the Unit to add [text removed for publication] to the value of their business. Institute Curie (Paris), applies this data mapping technique and the software that has been developed jointly with Leicester in clinical projects.

Submitting Institution

University of Leicester

Unit of Assessment

Mathematical Sciences

Summary Impact Type

Technological

Research Subject Area(s)

Mathematical Sciences: Pure Mathematics, Statistics
Information and Computing Sciences: Computation Theory and Mathematics

Knowledge Transfer of Innovative Cloud Computing Technologies

Summary of the impact

This case study reports our work on the development, application and dissemination of innovative cloud-based technologies to industrial problem domains. First, decentralised scheduling is implemented within federated Clouds, to facilitate the new drug discovery process for a global pharmaceutical company. Second, multi-objective approaches to the management and optimisation of video processing and analysis workflows in distributed environments is described in the context of an SME organisation that is developing new products, services and markets. Both of these examples have attracted, and continue to attract, commercial funding, and demonstrate the efficacy of knowledge transfer into industry from University of Derby (UoD) research.

Submitting Institution

University of Derby

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Technological

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing, Computation Theory and Mathematics, Information Systems

A new product for creating annotated data sets within smart environments

Summary of the impact

[text removed for publication], a developer of high-precision medical devices, have produced a new data annotation tool ([text removed for publication]) based on research in CSRI on data storage formats and activity recognition for applications within smart home environments. Within [text removed for publication] stereo-based cameras record activities in a specified environment (e.g. kitchen) which are then annotated using user-based pre-configured activity labels (e.g. prepare meal, wash dishes). [text removed for publication] is currently used by [text removed for publication] users and has yielded additional sales worth [text removed for publication]. [text removed for publication] have employed [text removed for publication] additional technical development staff to extend [text removed for publication] functionality, and through an MoU [text removed for publication] now supports automated annotation based on CSRI's research on activity recognition.

Submitting Institution

University of Ulster

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Technological

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing, Information Systems

Electronic monitoring of dairy herds increases efficiency and reduces costs for UK and EU farmers

Summary of the impact

Research undertaken at Strathclyde during 2006-2009 produced a decision support platform combining artificial intelligence with low power wireless sensor technology, which was capable of alerting farm staff to animal conditions requiring human intervention. ETS Ltd, a privately owned University Spin-out company was founded in 2009 to develop and market the new technology, and now employs 7 full time staff. Since 2010 more than 250 farms in the UK and Europe have adopted the technology, enabling them to reduce operating costs, maximise milk revenue, with an estimated increase of £10k per 100 cows per annum. The new technology has also improved the performance of other existing businesses and has helped retain jobs in the supply chain in Scotland.

Submitting Institution

University of Strathclyde

Unit of Assessment

Electrical and Electronic Engineering, Metallurgy and Materials

Summary Impact Type

Technological

Research Subject Area(s)

Mathematical Sciences: Statistics
Engineering: Geomatic Engineering
Medical and Health Sciences: Public Health and Health Services

Culture evolutionary analysis for business and government

Summary of the impact

The research of Professor Bentley and colleagues has developed a novel and practical analysis that commercial and government organisations can use to extract social network `signatures' and collective decision patterns from available data that were never intended to measure social influence or `decision fatigue' directly (such as sales figures, trend popularity statistics or other `big data'). Since Bentley's arrival to Bristol University in 2011, this research and impact have proceeded in parallel, as for example in multiple publications with Paul Ormerod, who is co-director of Volterra LLP, an influential consulting company whose direction was informed by this research with Ormerod. Other research was published in trade magazines (e.g., refs [f, g] below) shortly after academic publication (1-6), which led other organisations to follow in applying the methods of data analysis. For example, in 2011-12 Sony Electronics Europe (via Anomaly Communications, London) contracted this analysis of their sales data to distinguish market segments characterised by consumers looking toward `expert' opinion, versus segments in which indiscriminate copying was more prevalent, which fundamentally steered the segment-specific marketing strategies.

Submitting Institution

University of Bristol

Unit of Assessment

Geography, Environmental Studies and Archaeology

Summary Impact Type

Societal

Research Subject Area(s)

Mathematical Sciences: Statistics
Information and Computing Sciences: Information Systems
Economics: Econometrics

Improving Social Care Call Centre Operational Effectiveness

Summary of the impact

Targeted Projection Pursuit (TPP) — developed at Northumbria University — is a novel method for interactive exploration of high-dimension data sets without loss of information. The TPP method performs better than current dimension-reduction methods since it finds projections that best approximate a target view enhanced by certain prior knowledge about the data. "Valley Care" provides a Telecare service to over 5,000 customers as part of Northumbria Healthcare NHS Foundation Trust, and delivers a core service for vulnerable and elderly people (receiving an estimated 129,000 calls per annum) that allows them to live independently and remain in their homes longer. The service informs a wider UK ageing community as part of the NHS Foundation Trust.

Applying our research enabled the managers of Valley Care to establish the volume, type and frequency of calls, identify users at high risk, and to inform the manufacturers of the equipment how to update the database software. This enabled Valley Care managers and staff to analyse the information quickly in order to plan efficiently the work of call operators and social care workers. Our study also provided knowledge about usage patterns of the technology and valuably identified clients at high risk of falls. This is the first time that mathematical and statistical analysis of data sets of this type has been done in the UK and Europe.

As a result of applying the TPP method to its Call Centre multivariate data, Valley Care has been able to transform the quality and efficiency of its service, while operating within the same budget.

Submitting Institution

Northumbria University Newcastle

Unit of Assessment

Mathematical Sciences

Summary Impact Type

Technological

Research Subject Area(s)

Mathematical Sciences: Statistics
Information and Computing Sciences: Artificial Intelligence and Image Processing, Information Systems

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