Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
A cost effective, self-calibrating, low maintenance pH sensor for an integrated approach to monitoring sea and drinking water, facilitating improvements in ocean, animal and human health (pHenom)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: United Kingdom
Call: SME instrument (H2020-SMEInst-2018-2020-2, 2018)
Start date: 2018-08-01
End date: 2020-09-30
Duration (months): 26.0
Total project cost (EUR): 1124210.0
EU funding (EUR): 786947.0
Participants: 1
Project status: CLOSED

ANB Sensors (ANB) is a company set up to develop the next generation of pH Sensors for oceanographic, source water and aquifer monitoring and water resource management applications. In a short period of time, ANB has won innovation awards and grant funding and registered intellectual property (IP) (3 patents pending with a further 5 patents in the filing stage) covering new, fundamental pH sensor technology. The key failing of existing pH sensors is the short life and high maintenance costs of the sensors, which is a result of reference electrode drift giving unreliable measurements. The impact of reference drift is that most current ISE sensors cannot be used for long duration monitoring, cannot be used autonomously in smart sensor networks and require frequent, labour intensive calibrations. The only solution to reference drift currently available is expensive manual calibration. ANB’s innovative pH sensor, the pHenom, is based on a voltammetric electrochemical technique, which utilises a pH responding molecule bound within a solid-state matrix. This is combined with a novel means of verifying the performance of the pHenom’s reference electrode through an additional in-situ electrochemical measurement. For the first time, the pHenom sensor provides a pH sensor that is capable of smart, networked sensing allowing companies and government funded agencies to use their scarce monitoring management resources more efficiently. ANB’s overall objective for this project, therefore, is to develop the pHenom technology to the point where it can be placed on the market as-soon-as-possible, through technology licensing and sales. To meet this objective, in this project ANB will develop and produce four commercial prototype sensor systems specifically tailored for the biggest pH sensor market, the water monitoring and management industry. These commercial prototypes will be used to demonstrate the operational advantages of the pHenom technology to gain market acceptance.

Keywords: ph sensors,self calibrating,energy efficient,low maintenance,smart
Computing Answers to Complex Questions in Broad Domains (DELPHI)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Computer science and informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: Israel
Call: ERC Starting Grant (ERC-2018-STG, 2018)
Start date: 2019-04-01
End date: 2024-03-31
Duration (months): 60.0
Total project cost (EUR): 1499375.0
EU funding (EUR): 1499375.0
Participants: 1
Project status: SUSPENDED

The explosion of information around us has democratized knowledge and transformed its availability for people around the world. Still, since information is mediated through automated systems, access is bounded by their ability to understand language. Consider an economist asking “What fraction of the top-5 growing countries last year raised their co2 emission?”. While the required information is available, answering such complex questions automatically is not possible. Current question answering systems can answer simple questions in broad domains, or complex questions in narrow domains. However, broad and complex questions are beyond the reach of state-of-the-art. This is because systems are unable to decompose questions into their parts, and find the relevant information in multiple sources. Further, as answering such questions is hard for people, collecting large datasets to train such models is prohibitive. In this proposal I ask: Can computers answer broad and complex questions that require reasoning over multiple modalities? I argue that by synthesizing the advantages of symbolic and distributed representations the answer will be “yes”. My thesis is that symbolic representations are suitable for meaning composition, as they provide interpretability, coverage, and modularity. Complementarily, distributed representations (learned by neural nets) excel at capturing the fuzziness of language. I propose a framework where complex questions are symbolically decomposed into sub-questions, each is answered with a neural network, and the final answer is computed from all gathered information. This research tackles foundational questions in language understanding. What is the right representation for reasoning in language? Can models learn to perform complex actions in the face of paucity of data? Moreover, my research, if successful, will transform how we interact with machines, and define a role for them as research assistants in science, education, and our daily life.

Keywords: natural language understanding,question answering,machine learning
Bayesian Uncertainty Quantification of Intelligent vehicles (BITS)

Framework: Horizon 2020 — Spreading excellence and widening participation
Programme: Widening participation and spreading excellence
Theme: Other Widening
Action type: Marie Skłodowska-Curie actions
Countries involved: Cyprus
Call: Widening Fellowships (H2020-WF-02-2019, 2019)
Start date: 2020-06-01
End date: 2022-05-31
Duration (months): 24.0
Total project cost (EUR): 157941.12
EU funding (EUR): 157941.12
Participants: 1
Project status: CLOSED

The study of intelligent vehicles (IVs) is an area developing very fast and has the potential to transform road transportation and personal mobility in the years to come. In order to evaluate and minimize risks in the dynamic environment of IVs, it is necessary to have an accurate representation of the system and the uncertainty; the system describing IVs will never be a perfect representation of the true physical process and relying on its accuracy may lead to unreliable estimations and predictions and hence lead to wrong decisions. We will take into account this discrepancy of the mathematical representation and the physical system and utilize a fully Bayesian approach to develop a novel Bayesian learning methodology enabling efficient decision-making such avoiding collisions, as well as robust fault diagnosis. By first analyzing and understanding the uncertainty of an individual IV, the aim is to move to the collective behavior of IVs. This methodology will be validated on a physical test-bed at the University of Cyprus. The proposed project is highly interdisciplinary and combines methods from Engineering (expertise of the supervisor) and Statistics (extensive experience of the ER whose research background blends with parallel developments in Computer Science such as Machine Learning). This fellowship will contribute to the boost and advancement of the ER's career and ensure a two-way transfer of knowledge by (1) enriching the ER’s research skills through a career development plan and (2) the ER will transfer to the host her expertise. The potential impact of the proposed Bayesian uncertainty quantification of IVs can be high and important for the society as a whole, as we are making a step to the right direction to make IVs part of our everyday lives. The project has been designed around a coherent plan with experiments that will examine specific research directions but will also provide valuable insights and draw conclusions on Bayesian learning for IVs.

Keywords: bayesian learning,gaussian processes,intelligent vehicles,connected and autonomous vehicles,statistical emulator,fault diagnosis,uncertainty quantification
Advanced User-centric efficiency metRics for air traffic perfORmance Analytics (AURORA)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Theme: Public-private partnerships
Destination: Single European Sky Air Traffic Management Research
Action type: Research and Innovation actions
Partnership: SESAR (Art-187)
Countries involved: Ireland,Spain,Sweden
Call: ATM Performance (H2020-SESAR-2015-1, 2015)
Start date: 2016-04-01
End date: 2018-03-31
Duration (months): 24.0
Total project cost (EUR): 829312.5
EU funding (EUR): 829312.5
Participants: 4
Project status: CLOSED

This project will propose advanced metrics to assess the operational efficiency of the ATM system (challenge of the topic ER-11-2015). These new metrics will be developed with the aim of encapsulating the airspace users’ operational objectives, considering fuel consumption, schedule adherence and cost efficiency of the flights. User-preferred trajectories will be defined as references for performance analysis purposes. AURORA will also propose metrics to measure how fairly the inefficiencies in the system are distributed among the different airspace users. The other main research area will consist of exploring and testing techniques borrowed from the data science and information management fields for the collection and aggregation of data. These techniques will allow AURORA to propose a new framework for ATM decision-making based on real-time performance monitoring of user-centric efficiency indicators, where the airspace users could take an active role. AURORA will validate all these advanced user-centric efficiency metrics (and the proposed methods to obtain them) at European and local level by comparing them with today’s Flight Efficiency indicator used by the Performance Review Commission. AURORA will also assess the benefits for the performance-oriented operational concepts (e.g. SESAR) of using the real-time ATM performance monitoring framework to identify opportunities to improve system efficiency and better cater for the users’ operational needs. The innovative method to assess the metrics will be based on defining a generic advanced trajectory-based airline cost model that captures, to the extent required for air traffic efficiency assessment, the impact of different aspects of the trajectory (e.g. fuel burn or departure and arrival times) on the airlines’ operational costs. The model will be characterized by not requiring sensitive information from the airspace users and by the fact that it will be applicable to both recorded and streaming data.

Keywords: efficiency,performance,indicators,airspace users,analytics,monitoring,decision making
Sustainable Processes and Optimized Technologies for Industrially Efficient Water Usage (SPOTVIEW)

Framework: Horizon 2020 — Industrial Leadership
Programme: Nanotechnologies, Advanced Materials, Advanced Manufacturing and Processing, and Biotechnology
Theme: Sustainable, resource-efficient and low-carbon technologies in energy-intensive process industries
Action type: Innovation actions
Countries involved: Spain,Germany,Finland,Greece,Belgium,France,France,France,Netherlands,Luxembourg,United Kingdom
Call: Systematic approaches for resource-efficient water management systems in process industries (H2020-SPIRE-2016, 2016)
Start date: 2016-10-03
End date: 2020-04-02
Duration (months): 42.0
Total project cost (EUR): 8122039.0
EU funding (EUR): 6600115.01
Participants: 17
Project status: CLOSED

The objective of the SPOTVIEW project is to develop and demonstrate innovative, sustainable and efficient processes and technology components, in order to optimize the use of natural resources, especially water, in three industrial sectors (Dairy, Pulp and Paper and Steel) contributing to 44% of industrial water usage in EU. This resource optimization (including water, energy, raw materials and additives) is a key issue to maintain production competitiveness and sustainability. A total of 14 existing and new technologies will be assessed during the project, including solid/liquid separation, ultrafiltration, deionization, biological treatment, disinfection and chemical heat pump. The technology components will be assessed in simulated or operational environment for 9 new water management practices in the three industrial sectors. Up to 7 selected technologies demonstrators are planned in real industrial environment. The implemented process and technology will be evaluated in terms of environmental impacts and benefits, generated by achieving the SPOTVIEW targets (20% to 90% reduction of water usage, wastewater emissions, chemicals and energy use). The SPOTVIEW consortium covers the whole value chain, from technology development, assessment, supply and industrial applications in each targeted sector. Economic exploitation of the proposed technologies is pursued through a well described business case scenario and market penetration strategy. The market opportunities for future services and technology products beyond the SPOTVIEW project will generate up to 2800 new equipment and 7000 new jobs in Europe. The expected gains for the industrial sectors generated by the recovery of by-products and by energy, chemicals and additives savings represent annually 1.53b€ for Europe. The generated production capacity increase by companies has been estimated at 22.8b€. Dissemination and training activities are planned to maximize the impact of the project.

Keywords: separation technologies,deionization,ultrafiltration,water reuse,heat pump,valuable substances recovery,microbial control,modelling,water footprint,life cycle assessment,competitiveness
Peer effects and endogenous network formation (PEERS)

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: Economic Sciences
Countries involved: Spain
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2014, 2014)
Start date: 2015-06-01
End date: 2017-05-31
Duration (months): 24.0
Total project cost (EUR): 158121.6
EU funding (EUR): 158121.6
Participants: 1
Project status: CLOSED

The aim of this project is to develop a theoretical and empirical framework to simultaneously study network formation and peer effects in education. The problem is important from a methodological perspective, as there do not exist general purpose estimatable models of social dynamics in Economics which treat the network formation process as endogenous and simultaneously contemplate network effects on behaviour and its feedback on the network formation process. The possibility of understanding the formation of social networks in terms of the characteristics of the agents forming links is severely limited in most applications by the presence of peer effects that alter these characteristics. Conversely one of the main difficulties in measuring peer effects in any context is that peer groups are endogenous. This project will have two main components (1) a theoretical component and (2) an empirical/experimental component. The theoretical component aims to construct and study in detail the properties of some models of peer effects treating network formation endogenously. In the empirical/experimental component I will estimate and test the models by (a) Relying on two datasets, one of which already exists and one of which is under construction, and which I am currently using on two related projects and (b) Building a detailed longitudinal dataset including information on social network structure and various kinds of behaviours and attitudes using surveys and economic experiments .
“Family Making in India through Adoption or Reproductive Technology ” An interdisciplinary investigation of preference of Indian couples experiencing infertility regarding means of family formation (FaMInART)

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: Social Sciences and Humanities
Countries involved: Belgium
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2019-07-01
End date: 2021-12-31
Duration (months): 24.0
Total project cost (EUR): 172800.0
EU funding (EUR): 172800.0
Participants: 1
Project status: CLOSED

The goal of this research project is to understand the socio-cultural and regulatory factors influencing preference of married couples in India suffering from infertility or subfertility regarding means of family formation. I will concentrate on two approaches to family formation; adoption of a child(ren) and assisted reproductive technologies (ARTs) using gamete (egg and/or sperm) donation. The study will focus on Indian couples who are residents of India and exclude members of the Indian diaspora who travel to India seeking adoption and/or ARTs. The objective of the research project will be achieved through three interconnected work packages each with specific research questions and methodology. The first work package involves a systematic literature review of factors influencing uptake of adoption as a means of family formation in India and globally. The second work package comprises of a normative analysis of Indian regulatory frameworks on adoption and use of ARTs (using gamete donation) in comparison to key international and European regulations. The last work package is designed to explore values, decision making process and experience of intending Indian parents regarding their chosen means of family formation using qualitative research methods. The insights generated from this project will be relevant for evidence based regulatory approaches to ARTs and adoption not only in India and other low-resource countries but also for global regulation of cross-border reproductive care. This interdisciplinary research project will be situated at the Bioethics Institute Ghent (BIG) with a secondment to the department of Reproductive Health and Research (RHR) at WHO Geneva for four months at the end.

Keywords: adoption,assisted reproductive technologies,decision making,empirical ethics,family formation,gamete donation,grounded theory,india,regulatory frameworks
New Sustainable Fiber Production Technology (NewNormal)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Finland
Call: SME instrument (H2020-SMEInst-2018-2020-2, 2019)
Start date: 2019-10-01
End date: 2021-03-31
Duration (months): 18.0
Total project cost (EUR): 2791250.0
EU funding (EUR): 1953875.0
Participants: 1
Project status: CLOSED

Textiles industry is one of the largest consumers industries globally, generating €1.5 trillion annually. The overall consumption of apparel is on the rise, promising further growth to the industry. However, textiles industry is also one of the most polluting industries producing 1.2 billion tonnes of CO2 equivalent per year. Thus, the industry is under immense legislative pressure. In addition, there is a shortage of supply of raw materials. Natural fibers like cotton require massive amounts of water, whereas viscose production utilises hazardous chemicals. Oil-based alternatives, like polyester, are the largest contributors of plastic microfibers in oceans. These trends are forcing the textiles industry to actively look for alternative raw materials. If they cannot find one, their profits will drop significantly in the next decades. Finnish SME Infinited Fiber Company (IFC) has developed low-cost process for producing cellulose based fiber from textiles waste. The fiber product – called Infinited Fiber – is sustainable, affordable, and available in unlimited quantities. Unlike viscose and polyester, Infinited Fiber has the touch and feel of cotton, which is preferred by consumers. It is the only fiber that meets the industry needs. IFC has already built an industrial pilot for producing 50 tons of Infinited Fiber annually. The whole capacity of the pilot has been acquired by some of the biggest fashion brands in the world. More than 15 brands have tested the fiber product with extremely positive feedback. They are now looking forward to launching Infinited Fiber based consumer products. The NewNormal project will support the scale-up of Infinited Fiber production. As a result of the project, we will reach the commercialisation phase of Infinited Fiber.

Keywords: cellulose fiber,textile industry,post consumer waste,sustainable production process
ECOLORO: Reuse of Waste Water from the Textile Industry (ECWRTI)

Framework: Horizon 2020 — Societal Challenges
Programme: Climate action, environment,  resource efficiency and raw materials
Theme: Enabling the transition towards a green economy and society through eco-innovation
Action type: Innovation actions
Countries involved: Italy,Belgium,Belgium,Belgium,Czechia,Netherlands,Netherlands,Netherlands
Call: First application and market replication (H2020-WATER-2014-two-stage, 2014)
Start date: 2015-06-01
End date: 2019-05-31
Duration (months): 48.0
Total project cost (EUR): 4822849.63
EU funding (EUR): 3748967.5
Participants: 8
Project status: CLOSED

Constant extraction of increasingly scarce fresh water puts a vital demand on increasing water-use efficiency in all sectors. The ECWRTI project will demonstrate the EColoRO concept on full industrial scale in two locations in the European textile industry. The EColoRO concept uses electro-coagulation (EC) combined with flotation to remove pollutants, colorants and chemicals from waste water very effectively. This unique feature enables using ultrafiltration and reverse osmosis membrane processes downstream in an optimized way. The key advantages are: - Total reuse of waste-water in textile industry reducing fresh-water intake by at least 75% - Low-cost and economically highly attractive - Very flexible, containerized and modular, easy scalable, low footprint, suitable for retro-fit, brownfield or greenfield application - Low energy use, no use of chemicals or flocculants, producing concentrated waste streams with very high re-use potential - Enabler for optimizing use of water, allowing for advanced energy and resource efficiency in the textile manufacturing processes EC and the EColoRO concept are currently proven at TRL 6. The ECWRTI project will run for 48 months and will deliver technological proof at TRL 8, ready for commercial uptake. It will further deliver the materials, analysis and tools needed for rapid commercial roll-out. The consortium consists of a focused and well-balanced team. The project is SME driven with EColoRO as coordinator and 6 partners from 3 EU member states with key know-how on waste water purification (VITO, EColoRO), textile technology and production (Inotex, Utexbel, Tintoria Pavese), electro-coagulation and engineering (Morselt), process technology, open innovation and project support (ISPT) and EU wide market access in the textile sector (Euratex). An advisory board with stakeholders from textile, process industry and waste water sectors will provide guidance, critical feedback and dissemination support.

Keywords: electro coagulation,innovative usage of existing technologies,ultra filtration