London, United Kingdom
London, United Kingdom

Middlesex University is a university in Hendon, North west London, England. It is located within the historic county boundaries of Middlesex from which it takes its name. It is one of the new universities and is a member of Million+ working group. As is the case with many former polytechnics, Middlesex was formally organised as a teaching institution in 1973, yet can trace its history back to 19th century.Since 2000, the university has been reducing the number of campuses dotted around London’s North Circular Road in an effort to cut costs and provide a better student experience by consolidating most of the university at the flagship campus in Hendon. As of the 2013 academic year, its estate strategy which has cost £150 million has now concentrated the university on one site in north London.In 2012 the university re-structured its academic schools in order to align them more closely with the needs of industry. Courses at Middlesex are now delivered by the schools of Business, Law, Art and Design, Health and Education, Media and Performing Arts and Science and Technology, alongside the university’s Institute for Work Based Learning. Wikipedia.


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Grant
Agency: European Commission | Branch: H2020 | Program: SGA-RIA | Phase: FETFLAGSHIP | Award Amount: 89.00M | Year: 2016

Understanding the human brain is one of the greatest scientific challenges of our time. Such an understanding can provide profound insights into our humanity, leading to fundamentally new computing technologies, and transforming the diagnosis and treatment of brain disorders. Modern ICT brings this prospect within reach. The HBP Flagship Initiative (HBP) thus proposes a unique strategy that uses ICT to integrate neuroscience data from around the world, to develop a unified multi-level understanding of the brain and diseases, and ultimately to emulate its computational capabilities. The goal is to catalyze a global collaborative effort. During the HBPs first Specific Grant Agreement (SGA1), the HBP Core Project will outline the basis for building and operating a tightly integrated Research Infrastructure, providing HBP researchers and the scientific Community with unique resources and capabilities. Partnering Projects will enable independent research groups to expand the capabilities of the HBP Platforms, in order to use them to address otherwise intractable problems in neuroscience, computing and medicine in the future. In addition, collaborations with other national, European and international initiatives will create synergies, maximizing returns on research investment. SGA1 covers the detailed steps that will be taken to move the HBP closer to achieving its ambitious Flagship Objectives.


The overall aim of this project is to create an International Network for Comparative Analysis of Social Inequalities (INCASI) with 19 universities, 10 from Europe and 9 from Latin America. The purpose is to conduct comparative research in the area of social inequalities. Through this network we hope to foster a space for collective reflection and the development of synergies between network partners that allow us to undertake innovative studies whose outputs have an impact on academic and policy debates on the subject. The project will also contribute to informing the design of public policies to tackle social inequalities. In so doing, we aim to contribute innovative solutions that improve citizens living standards, reduce social inequalities and promote social justice. This is in line with Horizon 2020s objectives. From this perspective, the whole project is structured on the basis of the following four pillars: 1) Substantive background and explanatory models of social inequalities which comprises eight thematic axes integrated in a model of analysis called AMOSIT (Analytical Model of Social Inequalities and Trajectories). 2) Methodology for the analysis of social inequalities 3) Social policies to counteract social inequalities 4) Gender inequalities transversal perspective To achieve our objectives we organize the proposal chronologically through five work packages: 1) Compilation: to review the accumulated scientific capital that exists among networks members. 2) Construction: AMOSIT model. 3) Innovation: to propose a new theoretical and methodological perspective on social inequalities. 4) Projection: to planning the sustainability of the network through two specific lines of action in research and teaching, and to disseminating-communicating project outcomes. 5) Management: Organization and coordination of INCASI network activities.


Grant
Agency: European Commission | Branch: FP7 | Program: CP-IP | Phase: SEC-2013-1.6-4 | Award Amount: 16.64M | Year: 2014

The purpose of Project VALCRI is to create a Visual Analytics-based sense-making capability for criminal intelligence analysis by developing and integrating a number of technologies into a coherent working environment for the analyst we call the Reasoning Workspace. Conceptually, the Reasoning Workspace comprises three areas: (i) a Data Space which will enable an analyst to see what data and themes exist, (ii) an Analysis Space to which data can be brought into to carry out various computational analyses including statistical and text analysis, and (iii) a Hypothesis Space that will enable the analysts to assemble their evidence into coherent arguments that lead to meaningful and valid conclusions. The user interface will be rooted in the concepts of Visual Analytics the emerging science of analytical reasoning facilitated by visual interactive interfaces (Thomas and Cook, 2004), and specially designed to support the interactive dynamics (Heer and Shneiderman, 2012) required to enable real-time analytic interaction with data. The design of the user interface will move away from the traditional windows and list of lists views for presenting data, and instead to create information objects that may be directly manipulated and freely organised visuo-spatially by the analysts so that location and spatial groupings have meaning and can be manipulated directly by selection and dragging; or we can initiate Boolean operations on the content of the two or more clusters by dragging one cluster onto another. In addition, the presentation of multiple views of the information objects, in the form of network graphs, timelines, geo-spatial etc. can lead to further insight, especially when interactivity is enabled. This tight coupling between visualisation and computation is crucial for developing and maintaining cognitive momentum, the train of thought that enables creativity and sense-making.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: FCT-16-2015 | Award Amount: 3.42M | Year: 2016

Organized Crime and Terrorist Networks (OC/TN) are a major challenge for the European Union and many different stakeholder groups are involved in creating awareness, preventing, identifying and intervene in case of risk or threat. But in order to develop better strategies and instruments, we still need a deeper understanding of these phenomena. TAKEDOWN therefore aims at generating such novel insights on OC/TN. In order to meet this challenge and to investigate this complex field of research a multidimensional modelling approach is used. The resulting, proprietary TAKEDOWN Model describes social, psychological, economic aspects as well as further dimensions, activities and response approaches. A comprehensive empirical research combined with European and international expert knowledge ensures a valid and intuitive model. The TAKEDOWN Open Information Hub targets first-line-practitioners and provides modular solutions and inductive materials. The public web platform helps individuals to navigate to the right third party reporting and help lines including an innovative crowd reporting application to report digital OC/TN cases. The TAKEDOWN OC/TN Professional Solution Platform consists of various modules for law enforcement and homeland security departments. Designed with a flexible Platform as a Service (PaaS) architecture it combines knowledge materials and digital security solutions. Via the TAKEDOWN Security Dashboard information streams of native and third party applications are combined in an identification and issue management cockpit. The TAKEDOWN Professional Advisor supports experts on the selection of relevant approaches and security solutions to tackle OC/TN. With this multi-level approach, TAKEDOWN will force a better understanding of OC/TN, develop modern approaches and solutions, and will finally lead to a more efficient and effective response on OC/TN and strengthen social cohesion at pan-European level.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: SC1-PM-14-2016 | Award Amount: 2.08M | Year: 2017

The groundbreaking objective of CARESSES is to build culturally competent care robots, able to autonomously re-configure their way of acting and speaking, when offering a service, to match the culture, customs and etiquette of the person they are assisting. By designing robots that are more sensitive to the users needs, CARESSES innovative solution will offer elderly clients a safe, reliable and intuitive system to foster their independence and autonomy, with a greater impact on quality of life, a reduced caregiver burden, and an improved efficiency and efficacy. The need for cultural competence has been deeply investigated in the Nursing literature. However, it has been totally neglected in Robotics. CARESSES stems from the consideration that cultural competence is crucial for care robots as it is for human caregivers. From the users perspective, a culturally appropriate behavior is key to improve acceptability; from the commercial perspective, it will open new avenues for marketing robots across different countries. CARESSES will adopt the following approach. First, we will study how to represent cultural models, how to use these models in sensing, planning and acting, and how to acquire them. Second, we will consider three (physically identical) replicas of a commercial robot on the market and integrate cultural models into them, by making them culturally competent. Third, we will test the three robots, customized for three different cultures, in the EU (two cultural groups) and Japan (one cultural group), on a number of elderly volunteers and their informal caregivers. Evaluation will be conducted through quantitative and qualitative investigation. To achieve its groundbreaking objective, CARESSES will involve a multidisciplinary team of EU and Japanese researchers with a background in Transcultural Nursing, AI, Robotics, Testing and evaluations of health-care technology, a worldwide leading company in Robotics and a network of Nursing care homes.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: ICT-26-2016 | Award Amount: 4.30M | Year: 2017

Dreams4Cars takes inspiration from the Simulation Hypothesis of Cognition notably in the sense of Hesslow and in particular from the idea that thoughts are chains of simulated actions and simulated perceptions. The main objective of Dreams4Cars is to set up an offline simulation mechanism in which robots, by recombining aspects of real-world experience, can produce an emulated world, with which they can collectively interact to safely develop and improve their Perception-Action systems, in particular focusing on the analysis of rare events. The Perception Action systems trained by simulations in this way will then be used for sensorimotor control in real interactions. The application domain of Dream4Cars is automated driving, which besides being a major economic sector for the EU also poses the issue of developing systems capable of dealing with arbitrary and open-ended circumstances. Accidents are rare events and, to demonstrate that autonomous systems are safe enough (i.e. significantly safer than humans which is not achieved today at high and full automation levels), extensive field operation tests would normally be required. The solution offered by Dreams4Cars, by focusing on variations of much more frequent near-miss accidents, can develop safe behaviours for hypothetical/unexperienced situations. Hence Dream4Cars will contribute by solving both the problem of discovering critical situations and the problem of updating safely the software. Dreams4Cars will compare the driving agents evolved by the simulation technology to a baseline agent which will have the same State of the Art skills developed by the latest EU project in driving automation (AdaptIVe), hence concretely verifying the added value of the robotic technology (with target TRL 6).


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: PHC-18-2015 | Award Amount: 5.54M | Year: 2016

Each year 15 million babies are born prematurely and many suffer from respiratory failure due to immaturity of the lung and lack of control of breathing. Although respiratory support, especially mechanical ventilation, can improve their survival, it also causes severe injury to the vulnerable lung resulting in severe and chronic pulmonary morbidity lasting in to adulthood. Heterogeneity of lung aeration, resulting in areas of lung over inflation and lung collapse, plays a crucial part in the risk of mortality and morbidity due to respiratory failure. This distribution of lung aeration cannot be detected by currently available bedside monitoring tools and imaging methods. Thus, an imaging technique for continuous non-invasive bedside monitoring of infants lung function is urgently needed. In order to address this, CRADL will use EIT technology to establish a monitoring tool for interventions in the paediatric population. Electrical impedance tomography (EIT) is a non-radiative, inexpensive technique that can facilitate real time dynamic monitoring of lung aeration, and recent studies have shown that it is effective in monitoring aeration in preterm babies. CRADL will show how EIT can provide new cost effective, easy to use, respiratory management tools and clinical protocols that can be universally adopted to reduce deaths and disability in preterm babies by delivering a tool that provides continuous, non-invasive, radiation free, bedside information on regional lung aeration and ventilation during daily clinical care of (preterm) infants and children with respiratory failure. CRADL will also assess the effectiveness, efficacy and safety of such a system in guiding respiratory management and supportive care of the most common causes of paediatric respiratory failure (respiratory distress syndrome, bronchiolitis and acute respiratory distress syndrome), with the final goal of reducing short and long term adverse effects of disease and its treatment in this populat


Grant
Agency: European Commission | Branch: H2020 | Program: MSCA-ITN-ETN | Phase: MSCA-ITN-2015-ETN | Award Amount: 3.88M | Year: 2016

Flood risk systems are characterised by physical and socio-economic processes acting at different space-time scales, by non-stationary and non-linear behaviour, and by a significant degree of interdependence between processes. This may lead to surprising developments and unanticipated side effects of risk reduction measures. A novel systems approach is needed that captures this dynamics and accounts for the interactions of the system components. We propose the ETN SYSTEM-RISK which aims at developing this systems approach for large spatial scales, from large river basins to the European scale. The research concept of SYSTEM-RISK builds upon the entire risk chain, from the source of hazard to consequences, and analyses the interactions and temporal dynamics in flood risk systems. In this way, the linear risk chain is replaced by a more realistic approach with interdependent links. SYSTEM-RISK exposes early-stage researchers (ESR) to all knowledge domains along the risk chain, and gives them, at the same time, the opportunity to build specific research profiles. The interdisciplinary setting and the focus on interactions and spatio-temporal dynamics of risk system will expand the mental models and lead to a new generation of creative scientists, able to transfer their systems perspective from flood risk systems to other fields. We bring together internationally leading groups in flood research with institutions from the non-academic main sectors exploiting flood research consultancy, insurance industry and governmental sector. Close interaction will support the ESRs in developing trans-disciplinary skills with an understanding of both fundamental science and application. SYSTEM-RISK will deliver a suite of methods and tools for assessing and managing flood risk across large regions. This will be of highest importance for the EU Flood Directive and Strategy on Adaptation for Climate Change due to the EUs key role in dealing with risks transcending national borders.

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