Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Interferometric inertial sensors for gravitational-wave detectors (InertialSensors)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Physics
Countries involved: United Kingdom
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2015, 2015)
Start date: 2016-12-02
End date: 2018-12-01
Duration (months): 24.0
Total project cost (EUR): 183454.8
EU funding (EUR): 183454.8
Participants: 1
Project status: CLOSED

The detection of gravitational waves is expected within the decade and it will start a new era in astronomy. A limiting factor for all earth-based gravitational-wave detectors is isolation from ground motion that limits both low frequency sensitivity and detector operation. We propose to develop a new kind of extremely low-noise inertial sensors using laser-interferometer readout that can drastically improve active seismic isolation systems. The interferometric readout developed at Birmingham has low noise, huge dynamic range, and highly linear readout. This combination of properties allows a radical redesign and simplification of the mechanical components of an inertial sensor, and the removal of many common sources of noise. The technology required to build these sensors has many potential applications outside the field. The experienced researcher, Dr Mow-Lowry, will lead the experimental work and manage the project under the guidance of Professor Freise, and by the end of the proposal he will have proven his ability to deliver key instrumentation, making the transition from scientific contributor to principal investigator. In the years following, he will be ideally placed to exploit the project outcomes through scientific collaboration and commercialisation.

Keywords: gravitational waves
Chip-scale INtegrated Photonics for the mid-Infra REd (INsPIRE)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Systems and communication engineering
Panel description: Electrical, electronic, communication, optical and systems engineering
Countries involved: Italy,France,France
Call: ERC Starting Grant (ERC-2014-STG, 2014)
Start date: 2015-04-01
End date: 2020-03-31
Duration (months): 60.0
Total project cost (EUR): 1498125.0
EU funding (EUR): 1296875.0
Participants: 4
Project status: CLOSED

Mid-infrared (mid-IR) spectroscopy is a nearly universal way to identify chemical and biological substances, as most of the molecules have their vibrational and rotational resonances in the mid-IR wavelength range. Commercially available mid-IR systems are based on bulky and expensive equipment, while lots of efforts are now devoted to the reduction of their size down to chip-scale dimensions. The demonstration of mid-IR photonic circuits on silicon chips will benefit from reliable and high-volume fabrication to offer high performance, low cost, compact, low weight and power consumption photonic circuits, which is particularly interesting for mid-IR spectroscopic sensing systems that need to be portable and low cost. In this context, the INsPIRE project will address a new route towards key advances in the development of chip-scale integrated circuits on silicon for the mid-IR wavelength range. The original idea is to use nonlinear optical properties in Ge/SiGe quantum well (QW) active devices combined with Ge-rich-SiGe waveguides. The objectives of the INsPIRE project are far beyond the state of the art, by targeting the monolithic integration of passive and active devices for operation in the 3 to 15 µm wavelength range. As a main cornerstone we will demonstrate an optical photonic circuit based on Ge/SiGe QWs relying on a mid-IR light emitter combined with a mid-IR spectrometer and a detector array. The integration will be performed using Ge-rich-SiGe waveguides allowing the extension of the wavelength range up to 15 µm. Such demonstration, which will constitute a breakthrough for establishing chip-scale circuits for the mid-IR photonics, requires a deep knowledge and understanding of Ge/SiGe optical properties. In particular, second- and third-order nonlinear optical properties of Ge/SiGe QW structures will be investigated in a wide spectral range from 3 to 15 µm.

Keywords: mid infra red,silicon photonics,germanium,quantum wells
Aerial Insights: facilitating access to aerial drone imagery services through novel and cost-effective data analytics solutions (Aerial Insights)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: SME instrument
Countries involved: Spain
Call: Open Disruptive Innovation Scheme (H2020-SMEINST-1-2016-2017, 2017)
Start date: 2017-12-01
End date: 2018-05-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Aerial Insights is a software company based in Spain whose main focus is on the development and operation of imaging services with drones. Created in 2015 by a team of experienced and successful entrepreneurs, the company launched its new platform in 2016 to provide drone operators an affordable and innovative solution to extract drone imagery information from aerial data. Drones are becoming more and more popular and rapidly growing throughout the world. Today, they are used in multiple professional environments ranging from agriculture, insurance, mining industry to aerial photography and monitoring. According to recent PWC study, the expected business and services associated to drones will represent 127B USD globally. Among these services, drones equipped with cameras and other sensors (aerial photography) will play the most important role. Processing drone data with existing solutions is today cost-prohibitive. Data processing indeed requires expensive software and hardware as well expertise in multiple highly technical areas. Overall, we estimate an investment of 25K/year is required for physical resources, software and man hours to establish and provide services. Available at an average retail price €29,99 per map since 2016, Aerial Insights is based on a unique cloud platform and set of artificial intelligence algorithms where drone pilots can upload aerial raw imagery (step 1), select the outputs needed depending on the type of sensors onboard (step 2) and receive the relevant information on a secured online account within a few hours (step 3). This new approach is faster, cheaper and more reliable. For example, Aerial Insights reduces the timeframe required to diagnose and pinpoint faulty cells in a solar farm from 2-4 weeks (using traditional solutions) to 1-2 days. Regarding the mining industry, several weeks of work of a land surveyor can be replaced by a 15-minute flight and a couple of hours of processing.

Keywords: drones unmanned aerial vehicles uav,aerial imagery,data processing and analytics,2d and 3d map generation
Disrupting ELectrochemical Processes with HIgh-Performance Power Supplies (DELPHIS)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Spain
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2018)
Start date: 2018-12-01
End date: 2019-03-31
Duration (months): 4.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Electrochemical [EC] industry has highly contributed to our societal progress by enabling development of important modern industrial processes, being established as a multibillion-dollar industry for many applications. Scientists and engineers have actively searched for innovation strategies to optimize the operation of these processes. At POWER INNOTECH (founded by former employees of MCIA Research Group) we have identified a huge business opportunity if we totally redesign the obsolete power electronics technologies developed in the 70’s, that have several drawbacks, i) efficiency losses ii) overhead costs associated to reactive power, iii) failure propensity and iv) lack of control strategies. We are committed to commercialize the next generation of Power Supplies targeted for EC applications with i) High-Efficiency, ii) High-Power Density , iii) Fault-Tolerant Feed-Back Control operation, and iv) Signal Monitoring and IoT connectivity , overcoming all drawbacks and shortcomings from conventional systems. We have developed an innovative, high-performance high-efficient Power Supply that will disrupt electrochemical applications worldwide by bringing the latest developments: i) Semiconductors from Silicon Carbide (SiC) and Gallium Nitride (GaN), ii) Planar Transformer, and iii) Advanced IoT Control allowing energetic audits in real-time. The unique selling points of DELPHIS include the reduction of i) energy losses in 35%, ii) 95% of the reactive power, iii) capital costs, and iv) Weight and Volume, everything with a high power density and a high-degree of modularisation. Power InnoTech has attracted attention among companies working with electrochemical processes. POWER INNOTECH has closed 4 sales, and have 5 orders signed, predicting 120 orders in the next 2 years. We aim to introduce a game-changer solution with a payback period <1 year. A fully industrialised DELPHIS technology will allow us to earn a position into the market and to guarantee company’s growth.

Keywords: silicon carbide,llc converters,solid state transformer,planar inductors,high power efficiency,electrochemistry,power factor correction,energy savings,environmental friendly,reactive energy
Speech recognition technology to enable people with speech disabilities to communicate freely (Talkitt)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: SME instrument
Countries involved: Israel
Call: Open Disruptive Innovation Scheme (H2020-SMEINST-2-2016-2017, 2017)
Start date: 2017-07-01
End date: 2019-12-31
Duration (months): 30.0
Total project cost (EUR): 1995473.75
EU funding (EUR): 1396831.63
Participants: 1
Project status: CLOSED

Over one million people around the world suffer from some form of speech disability. For many, everyday communication is a challenge and participating in social and professional activities can be impossible. As a result, people with speech disabilities often feel isolated and/or dependent on those around them. Existing augmentative and alternative communication devices are bulky and awkward to use, and expensive if seeking high levels of accuracy. In addition, attempts to convert these technologies to app format have been widely unsuccessful. Voiceitt has developed Talkitt, a simple app downloadable to any device which translates unintelligible sounds into clear speech in real time. Talkitt’s goal is to improve the quality of life of speech disabled people by fostering inclusion and independence and enabling communication through their own voice. Voiceitt is aiming to commercialise two versions of the Talkitt technology, one targeting mild impairments and one targeting severe. During the innovation project, Voiceitt will optimise both apps, scale-up compatibility, and perform a widespread market validation with organisations and end users in four different countries: Israel, the UK, Italy and Spain.

Keywords: augmentative and alternative communication,speech disability,communication,speech recognition,speech impairments,mhealth,medical technology,educational technology
An Information Theory of Simple Interaction (InfoInt)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Systems and communication engineering
Panel description: Electrical, electronic, communication, optical and systems engineering
Countries involved: Israel
Call: ERC Starting Grant (ERC-2014-STG, 2014)
Start date: 2015-03-01
End date: 2021-08-31
Duration (months): 78.0
Total project cost (EUR): 1323875.0
EU funding (EUR): 1323875.0
Participants: 1
Project status: CLOSED

Motivated by our recent progress in feedback information theory and its deep relations to stochastic dynamical systems, and inspired by natural phenomena such as bio-molecular interactions and human conversation, this research will explore the fundamental limits of information transfer via simple interaction. In the standard information theoretic framework, the problem of reliable communications is typically studied in an asymptotic unidirectional regime, where optimal performance is attained via complex codes employed over increasingly long time epochs. Here, we will investigate a markedly different paradigm where communicating parties are restricted to use simple finite-state rules to act and react on the fly. We will consider a broad spectrum of models ranging from feedback communications and two-way channels to multiuser setups and large homogeneous networks, and study measures of information transfer and dissipation, their relations to dynamical system contraction factors, and the fundamental tradeoffs between complexity and performance. While prominently theoretic, our investigation is expected to admit important practical applications and a cross-disciplinary impact. In communications, and especially in resource-limited systems such as wireless sensor networks where battery-life is a bottleneck, a breakthrough in the understanding of optimal interaction can lead to a paradigm shift in system design, yielding simpler, cheaper, more robust solutions. In Finance, where market behavior is a cumulative effect of local actions taken by individuals based on limited noisy observations, quantifying interaction and its relation to information propagation can enhance our ability to forecast and explain macro level phenomena. Finally, an information theoretic characterization of interaction in large networks can shed light on the underlying mechanisms governing various biological systems that are empirically amenable to cellular automata modeling.

Keywords: information theory,interactive communications,feedback communications,dynamical systems,posterior matching
Mobility trajectories of young lives: Life chances of transnational youths in Global South and North (MO-TRAYL)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: The Social World and Its Diversity
Panel description: Sociology, social psychology, social anthropology, education sciences, communication studies
Countries involved: Netherlands
Call: ERC Consolidator Grant (ERC-2015-CoG, 2015)
Start date: 2017-01-01
End date: 2023-06-30
Duration (months): 78.0
Total project cost (EUR): 1937500.0
EU funding (EUR): 1937500.0
Participants: 1
Project status: SIGNED

The objective of MO-TRAYL is to develop a better understanding of the relationship between migration and young people’s life-chances by studying youth’s mobility trajectories. How the life chances of youths, defined as their educational performance, psychological well-being and transitions into adulthood, are impacted by migration are of relevance for European cities that are faced with a growing youth population with migrant background. At the same time, cities in the Global South, where many migrants in Europe originate from, are faced with large portions of the population of minors who are living without at least one of their parents due to their parent’s migration. There is growing concern in both academia and policy about how these ‘stay-behind’ children are faring. Yet little is known about how migration impacts young people in the Global North and South in the medium-term, in part because our conception of young people’s mobility patterns has to date been overly simplified (either they move once, or they do not). This results in a lack of data that specifically looks at the different mobility patterns of young people and hardly any that has a longitudinal dimension. MO-TRAYL will break new ground by studying simultaneously youths in the Global South who have remained ‘at home’ and those who have migrated to Europe by making use of unique new longitudinal data collected in the Global South as well as collecting new data in the Global North that specifically traces the mobility trajectories, the resulting different family compositions along the way, and how both affect life chances. Through a transnational perspective in which family members and events spanning home and host countries are brought to bear on life chances, MO-TRAYL aims to re-conceptualize youth mobility and families and add a longitudinal dimension to the study of migration and life chance outcomes. The project focuses on Ghanaian children in Ghana, The Netherlands, Belgium and Germany.

Keywords: migration,transnationalism,transnational families,international development studies,sub saharan africa
Custom architecturally defined 3D stem cell derived functional human neural networks for transformative progress in neuroscience and medicine (MESO_BRAIN)

Framework: Horizon 2020 — Excellent Science
Programme: Future and Emerging Technologies (FET)
Theme: EIC Pathfinder
Destination: Novel ideas for radically new technologies
Action type: Research and Innovation actions
Countries involved: Spain,Germany,United Kingdom,United Kingdom,United Kingdom
Call: FET-Open research projects (H2020-FETOPEN-2014-2015-RIA, 2015)
Start date: 2016-09-01
End date: 2020-02-29
Duration (months): 42.0
Total project cost (EUR): 3225891.25
EU funding (EUR): 3225890.5
Participants: 7
Project status: CLOSED

The development of methods to isolate and generate human stem cells along with technology to selectively differentiate them into specific cell and tissue types has excited many with the promise of the ability to study human cell function and utilise them for regeneration in disease and trauma. However, to date, attempts to develop regenerative brain and central nervous system therapies have been disappointing, with the introduced stem cell derived neurons not integrating nor signalling physiologically with endogenous cells. A major confounding issue has been that derived neurons are grown in two dimensions, which does not mimic the in vivo three dimensional interactions nor the myriad developmental cues they would receive in vivo. We will develop functional three dimensional human stem cell derived neural networks of defined and reproducible architecture, based on that of a brain cortical module that will display in vivo connectivity and activity. The networks will be seeded on nano-scale designed femtosecond laser printed scaffolds using novel polymerisation methods that will allow electrical stimulation, simultaneous recording and light sheet imaging during development and at maturation to interrogate network function. Cells will be seeded at and will develop at specific, defined points on the network scaffold, enabling the growth of realistic and reproducible functional neuronal networks. The proposal seeks to provide fabricated reproducible scaffolds that can be produced on a large scale. These concepts are far outside what is currently pursued in the field. The development of such a technological platform will be foundational for a new era of biological and medical research based on human neural networks. Cellular neuroscience research and pharmaceutical drug discovery will be transformed and we envisage that within 15 years iPSC derived networks from individual patients will be re-implanted to treat conditions such as Parkinson’s disease, dementia and trauma

Keywords: two photon polymerisation,3d functional neural networks,scaffolds
REINFORCEMENT LEARNING FOR PREDICTIVE FAILURE-DETECTION AND PROACTIVE DATA MANAGEMENT ON DIGITAL STORAGE SYSTEMS (PREFAIL)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: Coordination and support actions
Countries involved: Cyprus
Call: European SME innovation Associate - pilot (H2020-INNOSUP-2020-02, 2020)
Start date: 2020-10-01
End date: 2022-02-28
Duration (months): 17.0
Total project cost (EUR): 121000.0
EU funding (EUR): 84700.0
Participants: 1
Project status: CLOSED

As the Digital Transformation of Europe, and the rest of the world, is rapidly picking up pace, the underlying physical infrastructure is similarly expanding to keep up with demand generated by over 2 billion connected computers and more than 30 billion smartphones, wearables and IoT devices. Nevertheless, Internet applications and services remain prone to inevitable hardware failures, that lead to data losses and increased maintenance costs. The primary problem lies with the cost of implementing data redundancy by constantly adding expensive hardware to cater to the needs of traditional data replication approaches (e.g. by always keeping copies of a file on multiple servers). With the assistance of an Innovation Associate specializing in Machine Learning, Algolysis Ltd aspires to extend its cloud-based storage device monitoring service (DriveNest - www.drivenest.com) with a robust state-of-the-art failure prediction engine. Reliably identifying soon-to-fail storage devices can be a transformative capability across the ICT sector, as a range of proactive data management and mitigation services can be built on top.

Keywords: machine learning,failure prediction,deep learning,reinforcement learning,storage devices
European Natural Airborne Disaster Information and Coordination System for Aviation (EUNADICS-AV)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Action type: Research and Innovation actions
Countries involved: Austria,Spain,Austria,Iceland,Germany,Italy,Belgium,Switzerland,Sweden,Finland,France,Netherlands,United Kingdom
Call: Addressing aviation safety challenges (H2020-MG-2016-SingleStage-INEA, 2016)
Start date: 2016-10-01
End date: 2019-09-30
Duration (months): 36.0
Total project cost (EUR): 7509318.75
EU funding (EUR): 7441813.75
Participants: 22
Project status: CLOSED

Aviation is one of the most critical infrastructures of the 21st century. Even comparably short interruptions can cause economic damage summing up to the Billion-Euro range. As evident from the past, aviation shows certain vulnerability with regard to natural hazards. The proposal EUNADICS-AV addresses airborne hazards (environmental emergency scenarios), including volcano eruptions, nuclear accidents and emergencies and other scenarios where aerosols and certain trace gases are injected into the atmosphere. Such events are considered rare, but may have an extremely high impact, as demonstrated during the European Volcanic Ash Crisis in 2010. Before the 1990s, insufficient monitoring as well as limited data analysis capabilities made it difficult to react to and to prepare for certain rare, high-impact events. Meanwhile, there are many data available during crisis situations, and the data analysis technology has improved significantly. However, there is still a significant gap in the Europe-wide availability of real time hazard measurement and monitoring information for airborne hazards describing “what, where, how much” in 3 dimensions, combined with a near-real-time European data analysis and assimilation system. The main objective of EUNADICS-AV is to close this gap in data and information availability, enabling all stakeholders in the aviation system to obtain fast, coherent and consistent information. This would allow a seamless response on a European scale, including ATM, ATC, airline flight dispatching and individual flight planning. In the SESAR 2020 Programme Execution Framework, EUNADICS-AV is a SESAR Enabling project (project delivering SESAR Technological Solutions). The project aims at passing a SESAR maturity level V2, which includes respective service validation activities, including validation exercises. Work will be also done to prepare a full V3 validation.

Keywords: airborne natural,technical hazards,data integration,4 d data analysis