Teesside University has its main campus in Middlesbrough in North East England. It has 21,830 students, according to the 2012/13 HESA student record. As well as the main university in central Middlesbrough, it also has a campus in Darlington named Teesside University Darlington. Wikipedia.
Agency: European Commission | Branch: H2020 | Program: SGA-CSA | Phase: INNOVATION | Award Amount: 2.34M | Year: 2015
A national service in support of recipients of the H2020 sme instrument and for the enhancement of innovation management in SMEs Innovation is a vital ingredient of growth and an important element of the future success of the UK. With some 95% of R&D and innovation conducted outside of the UK and many major and lead market shaping companies being of non-UK origin, access to knowledge, markets, skills and partners is increasingly taking place on a global basis. To ensure UK business stays competitive it is important that it is able to effectively access and exploit the growing global investment in research and innovation. Through EEN ENIW activities we will help businesses build collaborations and partnerships and access the finance, knowledge, skills, networks and customers to more rapidly move a concept through to commercialisation.
Agency: European Commission | Branch: H2020 | Program: IA | Phase: ICT-02-2014 | Award Amount: 6.71M | Year: 2015
GateOnes mission is to accelerate smart systems adoption by European SMEs in facilitating their access to advanced technologies for the development of innovative and smart solutions. GateOne offers Innovation as a Service to the benefit of SMEs in structuring a complete and adapted innovation chain to contribute to the Smartization of Europe. The concept is based on an innovative and pragmatic approach to cross the valley of death. Our Innovation Action is designed to enter efficiently into a new management paradigm in implementing critical size mechanisms. We will work on a unique Pan European portfolio of smart systems technologies to make them attractive and available for evaluation by a large panel of European SMEs. 20% of the portfolio will be related to bioelectronics technologies. In implementing the New Product Introduction process, our service will provide a collaboration framework between SMEs and RTOs, to progress from Lab to Market. From a complementary smart systems technologies portfolio we will work on 50 small scale projects to deliver innovation concept in the form of demonstrators. They will be produced at the only condition that an SME expresses interest and engages to enter into a testing phase. Our innovation service will allow low risk evaluation conditions. We will introduce product concept designed on a business case to meet SMEs expectations. We will structure, an adapted innovation chain, while validating the cost efficient manufacturability of the solution. A broad diffusion will make GateOne a European entry point of state-of-the-art technology for smart systems. Inherited from COWIN CSA success and commitment of RTOs to further apply and develop the COWIN approach, GateOne will lead to a major breakthrough for European competitiveness in engaging SMEs in the smartization wave. The support of the European Commission will validate the concept and prepare its sustainability with RTOs, industrials and private investors support.
Agency: European Commission | Branch: H2020 | Program: IA | Phase: EE-06-2015 | Award Amount: 5.14M | Year: 2016
The aim of the DR-BOB project is to demonstrate the economic and environmental benefits of demand response in blocks of buildings for the different key actors required to bring it to market. To achieve its aim the DR-BOB project will: Integrate existing technologies to form the DR-BOB Demand Response Energy Management solution for blocks-of-buildings with a potential ROI of 5 years or less. Demonstrate the DR-BOB integrated solution at 4 sites operating under different energy market and climatic conditions in the UK, France, Italy and Romania with blocks-of-buildings covering a total of 274,665 m2, a total of 47,600 occupants over a period of at least 12 months. Realise up to 11% saving in energy demand, up to 35% saving in electricity demand and a 30% reduction in the difference between peak power demand and minimum night time demand for building owners and facilities managers at the demonstration. Provide and validate a method of assessing at least 3 levels of technology readiness (1-no capability, 2-some capability, 3-full capability) related to the technologies required for consumers facilities managers, buildings and the local energy infrastructure to participate in the Demand Response Energy Management solution at any given site. Identify revenue sources with at least a 5% profit margin to underpin business models for each of the different types of stakeholders required to bring demand response in the blocks-of-buildings to market in different local and national contexts. Engage with at least 2,000 companies involved in the supply chain for demand response in blocks of buildings across the EU to disseminate the projects goals and findings.
Agency: European Commission | Branch: H2020 | Program: IA | Phase: LCE-02-2016 | Award Amount: 15.84M | Year: 2017
inteGRIDy aims to integrate cutting-edge technologies, solutions and mechanisms in a scalable Cross-Functional Platform connecting energy networks with diverse stakeholders, facilitating optimal and dynamic operation of the Distribution Grid (DG), fostering the stability and coordination of distributed energy resources and enabling collaborative storage schemes within an increasing share of renewables. inteGRIDy will: a) Integrate innovative smart grid technologies, enabling optimal and dynamic operation of the distribution systems assets within high grid reliability and stability standards b) Validate innovative Demand Response technologies and relevant business models c) Utilize storage technologies and their capabilities to relieve the DG and enable significant avoidance of RES curtailment, enhancing self-consumption and net metering d) Enable interconnection with transport and heat networks, forming Virtual Energy Network synergies ensuring energy security e) Provide modelling & profiling extraction for network topology representation, innovative DR mechanisms and Storage characterization, facilitating decision making in DGs operations f) Provide predictive, forecasting tools & scenario-based simulation, facilitating an innovative Operation Analysis Framework g) Develop new business and services to create value for distribution domain stakeholders and end users/prosumers in an emerging electricity market. inteGRIDy will impact on: a) operations by reconfigurable topology control & supervision b) market by providing new services c) customer by enhanced engagement through DR mechanisms d) transmission by novel forecasting scenarios for the MV/LV areas e) part of the production incorporating innovative storage targeting the optimum use of RES f) environment by CO2 reduction inteGRIDy approach will be deployed and validated in 6 large-scale and 4 small-scale real-life demonstration covering different climatic zones and markets with different maturity.
Agency: European Commission | Branch: FP7 | Program: BSG-SME | Phase: SME-2013-1 | Award Amount: 1.53M | Year: 2014
Sepsis is a life-threatening illness caused by the bodys overreaction to an infection and can be triggered either directly by infection or may occur after medical treatment or surgery.The mortality rate in patients admitted to hospital with severe sepsis is 28-50% and it remains the most prevalent cause of death in non-coronary Intensive Care Units (ICUs ). It is estimated that in the US ~$17 billion were spent annually treating sepsis in patients and a similar amount is spent across the EU. To reduce costs and provide better treatment to patients, early, accurate diagnosis is critically important. The CE-microArray project will utilize existing technology from clinical chemistry, microplate readers and cavity enhanced spectroscopy in a truly novel way to develop more sensitive, accurate, faster and more useful diagnostic platform. The project consortium comprises experienced SMEs from across Europe who have developed the concept but do not have the capability to undertake the required Research and Development to produce working prototypes in preparation for commercialization. To do this they require funding to pay third party R&D specialists to undertake the R&D. The project aims to produce a solution based on colorimetric detection that will be up to 100 times more sensitive, reducing the damage to patients with sepsis, allow sensitive and accurate detection of an increased range of biomarkers at lower cost and higher throughput. The market opportunity is estimated be greater than 1 billion and will bring a cumulative profit of ~38 million to the SME consortium over 5 years.
Agency: GTR | Branch: ESRC | Program: | Phase: Research Grant | Award Amount: 80.22K | Year: 2016
The trade in counterfeit goods is growing and has been linked to the operations of transnational organised crime (TOC). Much work and popular scrutiny has examined these flows of illicit goods. Less scrutinised are the financial mechanisms that enable them. To enter this criminal market at the wholesale level, organised criminals may need significant financial resources, from credit facilities to processing international transactions. Their need for financing can concern every stage of illicit supply, from production, shipping, to retail, be that small or large scale. However, while large sums of investment may be needed to enter a specific counterfeit market at the wholesale level, participation at the retail stage requires only modest resources; a process that has been simplified for criminal entrepreneurs as late-modern information and communication technologies (ICTs) and electronic commerce have developed over time and space. The appropriation of e-commerce could have a scaling effect allowing petty traders to act globally. The development of the counterfeit trade in cyber-space is significant. Yet little is known about how the financing of counterfeit goods is facilitated by digital technologies. There is also a general lack of information on the blurring of TOC into legitimate actors, which is particularly apparent in the context of the grey market in counterfeit goods. This project will address these issues. Drawing upon cross-disciplinary research expertise in social sciences (criminology and sociology) the humanities (law and geography), and working in collaboration with practitioners from the National Trading Standards e-Crime Team (NSeCT), the research seeks to investigate the financing of the trade in counterfeit goods. The study focuses specifically on financing and financing-related aspects of illicit markets in material counterfeit goods. Furthermore, while focusing on the UK context, it will contribute to our understanding of TOC by examining financial and physical flows in the counterfeit trade over borders. In this context, China, the dominant manufacturing force in the global economy with an advanced export infrastructure (see Intellectual Property Office and Foreign & Commonwealth Office, 2015), is part of the focus of this project. Lasting for twelve months, this exploratory projects key objectives are to: 1. Identify the various forms and sources of financing that are being used to trade in counterfeit goods. 2. Map the transnational physical and financial flows relating to the trade in counterfeit products, focusing in particular on UK-China. 3. Examine how the Internet and electronic commerce presents financial opportunities for counterfeiters and to explore how these online processes interact with the material trade in counterfeit products. 4. Consider the role of licit financial and business structures in relation to the illicit trade in counterfeit products. 5. Develop the teams network and expertise in a way that will enrich future research and enhance their contribution to enforcement and regulatory policy and practice on a larger scale beyond the scope of this exploratory project. The project will begin to develop an important knowledge base for law enforcement, regulatory agencies and policy makers. This will support informed decision making about resource allocation and measures to tackle counterfeiting, criminal financing and transnational organised crime. In addition, the project will establish a cross-disciplinary and cross-sector counterfeiting research network, an innovative methodology to research counterfeiting, and more generally provide an important contribution to the TOC knowledge base.
Agency: GTR | Branch: Innovate UK | Program: | Phase: Knowledge Transfer Partnership | Award Amount: 82.01K | Year: 2016
To establish technologies for growth and subsequent characterization of non culturable bacteria using minimal nutrient chambers. To genetically and phenotypically interrogate these bacteria for production of novel antimicrobials.
Agency: GTR | Branch: EPSRC | Program: | Phase: Research Grant | Award Amount: 100.46K | Year: 2016
Many industrial and commercial applications of planning technology have to reason about numbers. For example, in the area of autonomous systems and robotics, an autonomous robot often has to reason about its position in space, power levels and storage capacities. We call the internal representation that the robot has of its environment its model of the world. It is essential for these models to be easy to construct and ideally, they should be automatically constructed. This project concerns the subject of learning formal models of state-transition systems from observation of those systems operating. Consider an observer unfamiliar with the game of chess: by observing a sequence of moves, much can be learnt about the rules of the game. Watching a bishop for long enough demonstrates that only diagonal moves are possible for this piece. Domain model acquisition, or automated modelling, is the problem of allowing a computer to learn its own world model by observing actions. We will develop new methods of automated modelling for state transition systems with numeric state variables. And when we refer to domain model acquisition, we refer to the learning of any state transition system from example data that includes sequences of state transitions, whether that is in the context of automated planning, general game playing, interactive narrative, workplace rostering, or any other type of underlying problem. We first plan to learn models of domain with a common restriction of numeric variables in planning; the restriction to action costs. This restriction means that each ground action has a constant cost, and that the only numeric variable accumulates the sum of these individual action costs over the length of the plan. This accumulated value is the optimisation variable. Board games with action costs are those in which a score is accumulated throughout the play of the game. Successful completion of the first stage means that we have a domain model acquisition algorithm to learn models that include action costs. This class of planning domains is an important subset of numeric planning domains. However, many planning domains contain more complex numeric properties and, in particular, arbitrary numeric variables and constraints. The second stage, therefore, will concentrate on developing algorithms to learn these constraints. Completion of the project will allow models of many different problems to be learnt simply from observation. Examples include such things as capacity limits for certain resources, dimensional constraints for positioning items and strength of friendship level requirement to enable certain actions within a social-network aware interactive narrative setting.
University of Teesside | Date: 2015-09-03
Measuring expended energy of a moving body by providing at least one first sensor for measuring position data of a first part of the moving body, providing at least one second sensor for measuring relative position data of a second part of the moving body, using the first sensor to make a first measurement of the position of the first part over a period of time and subsequently calculating a global expended energy of the first part relative to a reference frame from the first measurement, using the second sensor to make a second measurement of the position of the second part over said period of time and subsequently calculating a relative expended energy of the second part relative to the first part from the first and second measurements.
Agency: GTR | Branch: Innovate UK | Program: | Phase: Knowledge Transfer Partnership | Award Amount: 80.79K | Year: 2016
To develop an automated platform for propagation and implementation of Mechanical & Electrical Planning design changes in construction projects.