There have been major advances in AI in the last five years, and their impact is already visible in the entertainment, automotive and manufacturing industries, but its transformative potential in early detection of PC is yet to be realized. PANC-CYS-GAN aims to address this bottleneck by developing innovative computational analytics that can learn PC-related latent representation of messy and complicated distributions of longitudinal multimodal data. It aims to provide a range of short- and long-term measurable global benefits harnessing UK’s positioning in health-informatics and artificial intelligence at the world stage to develop health technology emphasising holistic approach. Information such as, but not limited to, demographic, lifestyle, medical conditions, pathology and blood/urine tests are routinely collected. We hope by integrating host of such routinely collected information with medical imaging data through a Generative Adversarial (GAN) model we can potentially help in triaging patients better. Coordinator: Edge Hill University (PI) Academic Partners: Quenn Mary University of London (QMUL); University College London (UCL); University of Hertfordshire and Manchester Metropolitan University (MMU)
Prof Yonghuai Liu (PI) and Dr Ardhendu Behera, EHU; Prof Doonan and Dr Williams, Aberystwyth University
Description
Wheat is a major cereal crop and is globally important as a staple source of nutrients for around 40% of the world’s population (Giraldo, et al (2019)) with more than 700 million tonnes of grain produced annually (FAO report 2020: http://www.fao.org/worldfoodsituation/csdb/en/). There is widespread interest in estimating the number of ears per unit area (Ferrante et al., 2017) as this is a key yield component. Computer vision can estimate this and determine yield from crop images (Tan et al., 2020). However, accuracy and usability leave much room for improvement and most techniques can only count numbers of ears, not measure their shape and size. Therefore, manual data collection, involving visual inspection of the standing crop is still a gold standard for the validation of semi-automatic (Tan et al., 2020) and automatic methods (Sadeghi-Tehran, et al (2019)). This process is labor-intensive, error prone and time-consuming. The proposed approach aims to address this in a novel way by advancing state-of-the-art image processing and computer vision techniques with an effective user interface to facilitate high-throughput measurement of ears or the equivalent structures in a variety of cereals. Coordinator: Edge Hill University (PI) Academic Partners: Aberystwyth University
The potential of Big Data & Machine Learning for process improvement/scale-up is largely underutilized. We aim for a data-driven approach that guides decision-making and virtualizes the data we generate and store. Our new approach will improve yield and quality of our existing production processes and accelerate novel product development. Business embraces digital transformation to establish a data driven organization. This will embed advanced data analysis across functions to advance in higher sustainability through higher productivity. Therefore, this project will go for the identification of key parameters affecting process performance and product quality, which will help to debottleneck the limiting resources in major business areas. The biggest value of this project will be to further develop the missing tools to improve processes by machine learning algorithms in real-time.
Erasmus+ Strategic Partnerships – European Commission
Amount
Edge Hill University share: €56,235; Total: €449,685
People involved
Dr Stephen Kelly, Dr Peter Vangorp
Description
The aim of this project is to identify the Purchasing and Supply Management (PSM) skills that are likely to prevail in the modern network economy and those that are newly added to the profile of a European purchaser to develop an Industry4.0 PSM Skills framework; to develop a module-based course for higher education to teach these skills; and to develop new gamification and playful interaction-oriented didactical elements for the purpose of a student-centred teaching approach, including a gamified massive open online course (MOOC). Coordinator: University of Twente, Netherlands. Partners: Technical University of Dortmund, Germany; Lappeenranta-Lahti University of Technology, Finland; University of Economics in Bratislava, Slovakia.
Skills Bootcamp: Cloud Computing and Data Analytics
Edge Hill University share: £344,648; Total: £8,654,670
People involved
Prof Ella Pereira, Prof Nik Bessis
Country range group
Project title
Country Range Group
Dates
2019 – 2022
Funding source
Knowledge Transfer Partnership – Innovate UK
Amount
£238,000
People involved
Dr Marcello Trovati, Dr Charles Knight, Prof Nik Bessis
Description
Country Range Group (CRG) is a food service buying group for UK based food wholesalers. Its purpose is to position members as food-service wholesalers of choice for retailers, caterers and brand-owners. A core theme of CRG’s strategy is driving growth through data driven capabilities. The aim of the KTP is to create a powerful SMART management customer insight system, designed around relevant business processes of CRG and the group members companies. This project will position CRG as a leading UK food buying group within their market segment.
BEC systems integration
Project title
Development of a scalable, cloud-based, software product infrastructure with novel data-driven stock control and dispatch applications.
Dates
2019 – 2023
Funding source
Knowledge Transfer Partnership – Innovate UK
Amount
£212,981
People involved
Prof Ella Pereira, Prof Marcello Trovati and Prof Nik Bessis
Description
BEC Systems Integration deliver a range of warehouse management and asset tracking software and hardware solutions, primarily to customers in the food and beverage, manufacturing and engineering industries. The KTP will drive BEC towards a long term market leading position to provide solutions for mid-sized manufacturers and distributors by overhauling the way they deliver their solutions and adding specific new capabilities.
UKIERI (UK-India Education and Research Initiative) – DST (Department of Science and Technology, India)
Amount
Edge Hill University share: £149,000; Total: £194,900
People involved
Dr Ardhendu Behera, Prof Yonghuai Liu, Prof Nik Bessis
Description
CHARM aims to become a clear front-runner in real-time unobtrusive monitoring of complex human activities as they progress by developing a sound and widely applicable context-aware recognition framework. This is a difficult problem involving computer vision (CV), big data and artificial intelligence (AI), with immediate applications to smart cyber physical systems/environments. The framework is targeted for the Advanced Driver-Assistance Systems (ADAS) for safe driving, Take-Over-Request (TOR) for the next generation intelligent autonomous vehicles, as well as more natural human-car/robot/machine interactions associated with many cyber physical systems. Coordinator: Edge Hill University (UK Lead), UK and Indian Institute of Science (IISc), Bangalore, India (India Lead) Academic Partners: University of Bristol, UK; Indian Institute of Technology (IIT), Madras, India
Edge Hill University share: £121,000; Total: £517,000
People involved
Prof Ella Pereira, Prof Nik Bessis
Productivity Innovation Centre
Project title
Data Analytics
Dates
2018-2020
Funding source
ERDF (led by PIC)
Amount
£20,540
People involved
Dr Marcello Trovati
Description
This is a cross-departmental activity (in collaboration with some members of the Business School) aiming to facilitate external business in the identification of innovative solutions and opportunities. The use of Big Data will enable the automated extraction and assessment for actionable information from potentially huge data with various formats.
Vehicular Cyber Security
Project title
Vehicular Cyber security
Dates
September 2018 – February 2019
Funding source
Global Car Manufacturer industry
Amount
£10,000
People involved
Prof Nik Bessis, Dr Marcello Trovati
Cyber security for IoT based healthcare applications
Project title
Cyber Security for IoT Based Healthcare Applications
Dates
March 2018 – March 2019
Funding source
Joint Academic Development Centres Grant, Department of Business, Energy and Industrial Strategy
Amount
Edge Hill University share: £13,000; Total: £38,000
People involved
Dr Chitra Balakrishna, Prof Nik Bessis
Description
The aim of this proposal is to establish a collaborative research link between University of Bahrain and Edge Hill University in cybersecurity area. The two institutions offer BSc and MSc programs in cybersecurity, in addition to conducting active research in the areas of cyber security and Internet of Things. This research link will directly enable to create a synergy between the two institutions’s academic and research activities. Edge Hill has recently concluded a successful project on cyber security funded by the Higher Education Academy (http://www.cyberedge.uk). The sustainable impact can be demonstrated through sharing both teaching and learning practices as well as research findings between the two institutions. This could lead to offering world-class training in cyber-security, in addition to joint MSc and PhD supervisions between the two institutions resulting in high-quality joint-publications. By establishing a long-term research relationship, the two institutions could mutually benefit from the resources, domain experts and industry partners to explore core cyber security research challenges through external research grants. This relationship could be further explored in form of student-exchange programs and delivering specialist cyber-security training to students and staff. Partners: Dr Wael Al-Medany (Co-I)
MOTHER
Project title
MOTHER: Maternal IoT Garment for Home-based Foetal Electro-cardiogram
Dates
February 2018 – September 2018
Funding source
eFutures Sandpit Award (EPSRC)
Amount
Edge Hill University share: £1,800; Total: £8,000
People involved
Dr Chitra Balakrishna
Description
This project aims to develop an innovative wearable IoT foetal electrocardiogram (FECG) device to provide a home-based solution for foetal monitoring. Women undergoing high-risk pregnancies require regular FECG monitoring to ensure the baby is not at risk. At present most FECG solutions are not home-based and only available onsite at hospitals. The few home-based FECG products in the market, however, are not suitable for daily usage due to the limited wearability. With advanced printed electronics and electric potential sensors embodied seamlessly in a garment worn for the comfort of the pregnant mother, our proposed technology will provide non-invasive continuous and reliable FECG monitoring to ensure safe foetal development. Partners: Dr. Jerry Luo, Cranfield University (PI); Rodrigo Aviles-Espinosa, University of Sussex (Co-I)
Edge Hill University share: 472,988 €; Total: 4,499,446 €
People involved
Dr Yannis Korkontzelos, Dr Georgios Kontonatsios, Prof Nik Bessis
Description
A 3-year H2020 project focusing on evolving scalable architectures for persistence, analytics and monitoring of large volumes of hybrid data. The objective is to design and develop innovative text mining and big data processing methods to be integrated in data persistence architectures. Coordinator: The Open Group, UK Academic Partners: University of York, UK; University of L’Aquila, Italy; Centrum Wiskunde and Informatica, Netherlands; University of Namur, Belgium Industrial Partners: Volkswagen AG, Germany; GMV, Spain; Alpha Bank, Greece; Nea Odos, Greece; Institut fur angewandte Systemtechnik Bremen GmbH, Germany; Contemporary Learning Management Systems, Greece
Assessing the nature and causes of coastal dune evolution
Project title
Assessing the Nature and Causes of Coastal Dune Evolution
Dates
2018 – 2020
Funding source
Natural Environment Research Council (NERC)
Amount
Edge Hill University share: £10,000; Total: £354,354
People involved
Dr Huaizhong Zhang
Description
Partners: Dept of Geography, Edge Hill University; University of Nottingham; Ulster University
Edge Hill University share: 462,832 €; Total: 4,488,179 €
People involved
Dr Yannis Korkontzelos, Prof Nik Bessis
Description
The aim of CROSSMINER is to deliver an integrated open-source platform that will support the development of complex software systems by enabling monitoring, in-depth analysis and evidence-based selection of open source components and facilitating knowledge extraction from large open-source software repositories. Coordinator: The Open Group, UK Academic Partners: University of York, UK; University of L’Aquila, Italy; Centrum Wiskunde and Informatica, Netherlands; Athens University of Economics and Business, Greece; Bitergia, Spain Industrial Partners: OW2 consortium, France; Frontendart, Hungary; Softeam, France; Unparallel, Portugal; Eclipse Foundation, Germany
Dr Chitra Balakrishna, Dr James Coleman, Prof Daniela Romano
Description
The shortage of cyber-security professionals is universal and on-going. Fresh graduates often do not possess the readiness to apply their skills to real-world scenarios as employers demand. This project bridges the skills-gap between theory and practice. Using innovative pedagogical practices (gamification and problem-based learning), a self-directed immersive learning environment would be produced to train employable cyber-security professionals. The resources will be hosted on the cloud: CyberGaTE using the innovative concept of ‘Classroom as a Service’. The project will engage employers, higher education institutions, students in UK and Europe to build and assess CyberGaTE’s effectiveness, disseminating good practice.
Cyber security knowledge exchange
Project title
Cyber Security Knowledge Exchange – Creation of industry-led problem based learning scenarios and a student-led model for knowledge exchange with SMEs
Dates
November 2014 – February 2016
Funding source
Higher Education Academy
Amount
£74,734
People involved
Dr Chris Beaumont
Assisted living technology
Project ttitle
Assisted Living Technology – Review regarding education and qualifications to support implementation of Assisted Living Technology
Dates
September 2014 – April 2015
Funding source
NHS Liverpool Clinical Commissioning Group (CCG)
Amount
£6,000
People involved
Dr Dave Lyons, Prof Ella Pereira
Business insight 3
Project title
Business Insight 3
Dates
June 2014 – date
Funding source
Knowledge Transfer Partnership – Innovate UK
Amount
£113,783
People involved
Prof Mark Anderson
HistorySpace
Project title
HistorySpace
Dates
January 2014 – date
Funding source
Brock University
Amount
£18,000
People involved
Prof Mark Anderson, Prof Ella Pereira
Description
The aim of the project, in collaboration with Brock University in Canada, is to develop software that will allow historians to create three dimensional representations of historical buildings.
3D parametric modelling
Project title
Creating a 3D Parametric Modelling Community Environment
Dates
July 2017 – January 2018
Funding source
Research Investment Fund (RIF)
Amount
£13,916.50
People involved
Prof Mark Anderson, Prof Ella Pereira, Mr Brian Farrimond
Description
The 3D Parametric Modelling Project at Edge Hill University Computer Science is developing applications that enable people who have no special skills in 3D modelling to create quickly complex, realistic and dynamic models.
Human activity and behaviour understanding: dimensions of human-robot social interaction
Project title
Human Activity and Behaviour Understanding: Dimensions of Human-Robot Social Interaction
Dates
June 2017 – August 2017
Funding source
Student Opportunity Fund (SOF)
Amount
£7,328.47
People involved
Dr Ardhendu Behera, Dr Hui Fang and Dr Georgios Kontonatsios
Description
Human-robot social interaction plays a significant role to help aged, work with children having autism and patients finding physically or mentally difficult to perform tasks. The students will be involved in designing and developing such a framework for NAO robots within the department of Computer Science. They will be exposed to core skills of programming, software development and testing, data analysis and representation as well as soft skills (e.g. teamwork, communication, presentation, etc.) which would enhance their employability.
GATOR
Project title
GATOR: Gait Analysis of Total Hip Replacement
Dates
April 2017 – March 2019
Funding source
Research Institute Thematic Award (RITA)
Amount
£23,959
People involved
Prof Ella Pereira
Description
Identification of gait related changes in well-functioning and fixed, well-functioning but loose and symptomatic and loose total hip replacements Internal Partners: Dr Ben Langley (PI), Dr Henrike Greuel, Dr Richard Page, The Department of Sport and Physical Activity; Prof Paola Dey, Dr Julie Kirby, Faculty of Health and Social Care; External Partners: Mr Chris Whelton, Professor Tim Board, Dr Stewart Morrison, Dr Mary Cramp, Wrightington, Wigan & Leigh NHS Foundation Trust.
SmartPCI
Project title
SmartPCI
Dates
December 2016 – May 2017
Funding source
Research Investment Fund (RIF)
Amount
£15,000
People involved
Prof Ella Pereira, Mr Besim Mustafa
Description
Proof of concept study for developing and delivering PCI as SaaS. Partners: Prof Simon Rogers, Evidence-Based Practice Research Centre (EPRC)
Adaptive user interface: design and development of an eye-based human-computer interaction for people with varying severity of disabilities
Project title
Adaptive User Interface: Design and Development of an Eye-based Human-Computer Interaction (HCI) for People with varying Severity of Disabilities
Dates
October 2016 – September 2018
Funding source
Research Institute Thematic Award (RITA)
Amount
£24,112
People involved
Dr Ardhendu Behera
Description
The aim of this research to utilise this gaze behaviour for developing an interactive adaptive user interface which could be used by people with varying severity of the disabilities. The proposed research will focus on design and development of a gaze-contingent interface in which the amount of information presented to a user is automatically adjusted according to his/her information processing capability based on real-time eye-movement. Partners: Department of Psychology, Edge Hill University; Walton Centre NHS Trust; Southport and Ormskirk Hospital NHS Trust; Department of Psychological Sciences, Purdue University
GENEActive and actigraph accelerometers in older adults
Project title
GENEActiv and Actigraph accelerometers in older adults
Dates
January 2016 – December 2016
Funding source
Research Investment Fund (RIF)
Amount
£5,242
People involved
Dr Ardhendu Behera
Description
This proposed project aims to develop accurate and robust accelerometer activity mode and intensity thresholds to enable accurate measurement of free-living physical activity and sedentary behaviour in older adults. Partners: Department of Sport and Physical Activity, Edge Hill University
Autonomous intelligent feature for reducing driver’s interaction by understanding their behaviour pattern
Project title
Autonomous Intelligent Feature for Reducing Driver’s Interaction by Understanding their Behaviour Pattern
Dates
January 2016 – January 2017
Funding source
Research Investment Fund (RIF)
Amount
£14,920
People involved
Dr Ardhendu Behera
Description
The objective of the project is to develop a software solution for analysing and recognising activities of drivers. This is fundamental to in-vehicle cognitive technologies which will be a key component of how vehicles learn and reason to provide a better experience for the occupants and optimise its own performance.
Having a laugh
Project title
Having A Laugh – Making Transcription of Historical Texts Fun
Dates
9 November 2015 – 8 May 2016
Funding source
Research Investment Fund (RIF)
Amount
£10,034.21
People involved
Dr Mark Hall
Developing a virtual arts companionship of person-centred dance provision
Project title
Developing a Virtual Arts Companionship of Person-Centred Dance Provision
Dates
October 2014 – June 2015
Funding source
Research Investment Fund (RIF)
Amount
£7,476.12
People involved
Prof Ella Pereira
Description
This project looked at person-centred care, dance and technology with the aim to combine these things to support older people to lead full and independent lives. Partners: Prof Vicky Karkou (PI), Department of Performing Arts, Edge Hill University
PhD projects with external collaborations
Improving the performance of MANETs using machine learning
PhD project title
lmproving the Performance of MANETs using Machine Learning
Student
Yann Maret
Supervisory team
Dr Mohsin Raza, Prof Jean-Frederic Wagen, Prof Nik Bessis, Dr Junyuan Wang
Collaborator
Fribourg HES-SO: University of Applied Sciences and Arts Western Switzerland (Switzerland), armasuisse