Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Parsing low-resource languages and domains (LOWLANDS)

Framework: FP7 — Ideas
Programme: European Research Council
Theme: European research council
Destination: Starting grants
Action type: Support for frontier research (ERC)
Panel: The Human Mind and its complexity
Countries involved: Denmark
Call:  (ERC-2012-StG_20111124, 2012)
Start date: 2013-01-01
End date: 2018-03-31
Duration (months): 63.0
Total project cost (EUR): 1126183.2
EU funding (EUR): 1126183.2
Participants: 1
Project status: CLOSED

There are noticeable asymmetries in availability of high-quality natural language processing (NLP). We can adequately summarize English newspapers and translate them into Korean, but we cannot translate Korean newspaper articles into English, and summarizing micro-blogs is much more difficult than summarizing newspaper articles. This is a fundamental problem for modern societies, their development and democracy, as well as perhaps the most important research problem in NLP right now. Most NLP technologies rely on highly accurate syntactic parsing. Reliable parsing models can be induced from large collections of manually annotated data, but such collections are typically limited to sampled newswire in major languages. Highly accurate parsing is therefore not available for other languages and other domains. The NLP community is well aware of this problem, but unsupervised techniques that do not rely on manually annotated data cannot be used for real-world applications, where highly accurate parsing is needed, and sample bias correction methods that automatically correct the bias in newswire when parsing, say, micro-blogs, do not yet lead to robust improvements across the board. The objective of this project is to develop new learning methods for parsing natural language for which no unbiased labeled data exists. In order to do so, we need to fundamentally rethink the unsupervised parsing problem, including how we evaluate unsupervised parsers, but we also need to supplement unsupervised learning techniques with robust methods for automatically correcting sample selection biases in related data. Such methods will be applicable to both cross-domain and cross-language syntactic parsing and will pave the way toward robust and scalable NLP. The societal impact of robust and scalable NLP is unforeseeable and comparable to how efficient information retrieval techniques have revolutionized modern societies.

Keywords: natural language parsing,sample bias correction,semi-supervised learning,unsupervised learning
Economics of Matching Markets: Theoretical and Empirical Investigations (ECOMATCH)

Framework: FP7 — Ideas
Programme: European Research Council
Theme: European research council
Destination: Starting grants
Action type: Support for frontier research (ERC)
Panel: Individuals, institutions and markets
Countries involved: France
Call:  (ERC-2012-StG_20111124, 2012)
Start date: 2013-01-01
End date: 2018-09-30
Duration (months): 69.0
Total project cost (EUR): 1119000.0
EU funding (EUR): 1119000.0
Participants: 1
Project status: CLOSED

This project offers a theoretical and empirical investigation of matching markets. Matching is, broadly speaking, the study of complementarities, which explains the formation of coalitions. Matching models are found in many applied fields within Economics: Labour Economics, Family Economics, Consumer theory of differentiated goods (hedonic models), Trade, etc. Desirable properties of these coalitions, such as stability, lead to testable implications of the surplus that individuals generate in a match, allowing for structural estimation of matching models. The goal of this proposal is to expand the frontiers of the theory of matching to design a very general and highly flexible model of matching that will lend itself to estimation and thus lead to empirical findings in various fields of Economics. Based on promising work initiated by the PI, this proposal seeks to bridge the gap between the theory and the empirics of matching markets that was traditionally observed in this literature. Particular focus will be given to situations where stable outcomes may not exist (such as unipartite, or one-to-many matching models), frictions, taxes. In these cases, a thorough investigation is carried on what solution concept should be used, and what are the testable implications. Applications will be given to various empirical issues or policy relevant questions such as: - The nature of the complementarities between senior and junior employees within teams, - The role played by the marriage market in the problem of rural depletion in China, - The impact of CEO risk aversion on assignment to firms, and on the CEO compensation package, - The pricing of attributes of French wines.

Keywords: matching markets,structural estimation,assignment problem,stability,hedonic models
Transmission of innovations: comparison and modelling of early farming and associated technologies in Europe (EUROFARM)

Framework: FP7 — Ideas
Programme: European Research Council
Theme: European research council
Destination: Starting grants
Action type: Support for frontier research (ERC)
Panel: The study of the human past
Countries involved: United Kingdom
Call:  (ERC-2012-StG_20111124, 2012)
Start date: 2012-10-01
End date: 2017-09-30
Duration (months): 60.0
Total project cost (EUR): 1499832.0
EU funding (EUR): 1499832.0
Participants: 1
Project status: CLOSED

This project will investigate the transmission of farming and associated technological innovations (landscape use, pottery, lithics) in the western Balkans during the 6th and 5th millennium BC through a combination of new data collection (archaeological field work, access to museum collections and literature survey), analysis and agent-based modelling. The research area provides a unique opportunity to observe the creation and initial dispersal of the two cultural streams (inland and maritime) responsible for the introduction of farming across much of Europe. This project will be the first one to consider explicitly this process from the point of view of the transmission of innovations, that is how one becomes a farmer. The analytical work will characterise the competences and knowledge required for the transmission of each selected technological innovation. The agent-based modelling will aim at comparing these technologies together and weighing their respective impact in shaping the variability between the inland and maritime streams of neolithisation. Thanks to its combination of robust analytical work and modelling, this project will achieve the difficult balance between reflecting the complexity inherent to each technology, and the need for abstraction required for comparison.

Keywords: early farming - western balkans - agent-based modelling
A novel, integrated, wheelchair and hoist system (HOMEHOIST)

Framework: FP7 — Capacities
Programme: Research for the benefit of SMEs
Destination: Research for SMEs
Action type: Research for the benefit of specific groups
Countries involved: United Kingdom,Spain,United Kingdom,Jordan,Türkiye,Portugal
Call:  (FP7-SME-2012, 2012)
Start date: 2013-01-01
End date: 2014-12-31
Duration (months): 24.0
Total project cost (EUR): 1163575.4
EU funding (EUR): 892992.1
Participants: 6
Project status: CLOSED

The objective of the project is to produce a wheelchair with an integral hoist system. This will allow for more independent living, a reduced need for lifting and manual handling from carers and a reduction in the number of costly disability aids within the home. The Homehoist system will function initially as an everyday wheelchair, but will also be capable of lifting the user at certain positions within the home via the integrated hoist system rotate them through 180 degrees to the toilet, the shower, a sofa, or a bed. This will incorporate a stabilisation system and optional floor clamps will ensure the system is can operate under more demanding load conditions. If others areas of the home need to be accessed the hoist section of Homehoist is able to be detached and used independently, this will also improve transportation of the device by breaking the system down into two lighter more compact units. At Hi Tech Automation Limited we want to be sure that our business continues to develop. We make mechanical and lifting systems and consider ourselves experts in the field. With the help of AKS Medical, Technik, ARTI Electronics, HERI and IBV, we believe we have identified a novel design solution to the difficulty, comfort and costs associated with lifting a cerebral palsy patient. The primary aim of the project is to develop an integrated wheelchair and hoist system capable of independent use by a cerebral palsy patient with upper body strength. We will build and test a demonstration prototype. Post project we will invest in the design to develop it to production level.

Keywords: chair,homecare,assisted living,independance
Compact, Smart and Reliable Drive Unit for Fully Electric Vehicles (COSIVU)

Framework: FP7 — Cooperation
Programme: Information and Communication Technologies
Destination: ICT for a low carbon economy
Action type: Collaborative project
Countries involved: Sweden,Germany,Germany,Germany,Sweden,Germany,Germany,Slovenia
Call:  (FP7-2012-ICT-GC, 2012)
Start date: 2012-10-01
End date: 2015-09-30
Duration (months): 36.0
Total project cost (EUR): 5186130.0
EU funding (EUR): 3350000.0
Participants: 9
Project status: CLOSED

The project 'COSIVU' aims at new system architectures for drive-train by developing a smart, compact and durable single-wheel drive unit with integrated electric motor, compact transmission, full SiC power electronics (switches and diodes), a novel control and health monitoring module with wireless communication, and an advanced ultra-compact cooling solution. The advances over the current state of the art can be summarized as follows: • 20% higher energy efficiency and thus extended driving range due to dramatic reductions in the vehicle weight (30%) and in the losses in the power module (50%-70%) • Increased performance, flexibility as well as safety and reliability due to close hardware-in-the-loop control based on integrated sensors, novel analysis algorithms coded into the microcontroller within the smart drive allowing in-situ functional and health monitoring and the bi-directional wireless communication between each drive and a central computer • Reduced cost-of-ownership for the end-user due to prognostic maintenance advise, factor 2 increase in lifetime and uptime of the smart drive unit, and minimized usage of expensive mechanical parts and cabling. Within this project, these ambitious goals will primarily be demonstrated for commercial electric vehicles, which are even more demanding with respect to power performance, durability, and availability than other types of vehicles. In addition, the new architecture will be adapted to other vehicle platform such as vans, pick-up and even passenger cars. Specific and concrete examples will be given. Therefore, the feasibility of the novel drive-train architecture will be shown and demonstrated in a quite general way.

Keywords: drive-train unit,power electronics,sic components,system integration,power module packaging/cooling,functional/health monitoring,wireless communication in the drive-train,design-for-reliability
Collaborative and Adaptive Process Planning for Sustainable Manufacturing Environments (CAPP-4-SMES)

Framework: FP7 — Cooperation
Programme: Nanosciences, Nanotechnologies, Materials and new Production Technologies - NMP
Destination: Recovery Package: Public-Private Partnership (PPP) topics within NMP
Action type: Collaborative project
Countries involved: Sweden,United Kingdom,Greece,United Kingdom,Sweden,Spain,Germany,Germany,United Kingdom
Call:  (FP7-2012-NMP-ICT-FoF, 2012)
Start date: 2012-12-01
End date: 2015-11-30
Duration (months): 36.0
Total project cost (EUR): 4969112.4
EU funding (EUR): 3497957.0
Participants: 11
Project status: CLOSED

Innovative knowledge-based Computer Aided Process Planning (CAPP) is a key enabler to minimise cost, improve adaptability, responsiveness, robustness, and sustainability of manufacturing processes. This CAPP-4-SMEs project, planned for 36 month duration and 480 person-months, is aimed at enhancing the competitiveness of European companies, particularly SMEs, in sustainable manufacturing environment by: (1) collaborative and adaptive process planning against changes; (2) knowledge-based and integrated process simulation towards first-time-right processes; (3) event-driven function blocks for on-board adaptive process control; (4) machine availability monitoring for real-time job routing; and (5) a Cloud-based services platform for cost-effective and easy access over the Internet. The CAPP-4-SMEs Consortium is comprised of 11 partners (4 universities, 1 multi-national manufacturing company and 6 SMEs) from 5 European countries (Sweden, UK, Greece, Germany and Spain). The complementary expertise of the academic and industrial European partners in the project enables knowledge sharing, dissemination and exploitation of scientific findings, industrial applications and technical know-hows across the EU. Technical innovations will be achieved through collaborative RTD activities oriented towards industrial applications for factories of the future. Industry-relevant demonstration will be developed in the project as an important element for results validation using real-world cases from SMEs. Targeting to showcase 40% reduction in resource consumption, 30% improvement in process robustness and accuracy, and 30% increase in productivity by reduced cycle times under more reliable and efficient manufacturing conditions, the demonstration activities based on the RTD outcomes of the project will be geared to exploit future commercialisation opportunities throughout the extensive industrial networks of the Consortium, and to generate greater impacts in broader areas of the EU.

Keywords: process planning,machining,setup planning,machine utilisation,optimisation,real-time monitoring,adaptive control
eUropean naturalistic Driving and Riding for Infrastructure & Vehicle safety and Environment (UDRIVE)

Framework: FP7 — Cooperation
Programme: Transport (including Aeronautics)
Destination: Sustainable surface transport (INCLUDING THE �EUROPEAN GREEN CARS INITIATIVE�)
Action type: Collaborative project
Countries involved: Netherlands,Germany,Czechia,France,Spain,Germany,Belgium,France,Poland,France,Austria,United Kingdom,Israel,Sweden,Germany,Netherlands,United Kingdom
Call:  (FP7-SST-2012-RTD-1, 2012)
Start date: 2012-10-01
End date: 2017-06-30
Duration (months): 57.0
Total project cost (EUR): 10629926.34
EU funding (EUR): 7999965.0
Participants: 19
Project status: CLOSED

Road transport is indispensable for the exchange of goods and persons, but at the same time has severe negative consequences, among others related to road safety and environment. In order to meet EU targets, both the number of road crashes and vehicle emission levels need to be reduced substantially. For identifying the next generation of measures that will enable us to actually reach these targets, a far more in-depth understanding of road user behaviour is needed. The proposed UDRIVE project is building on the experiences of the PROLOGUE feasibility study and various Field Operational Tests (FOTs), and aims to contribute to developing this in-depth knowledge by: 1. Conducting a large-scale European Naturalistic Driving (ND) study; 2. Building one central database with the collected ND data; 3. Performing targeted analyses in the areas of: o crash causation factors and associated risks, o distraction and inattention, o vulnerable road users, o eco-driving; 4. Applying the findings in four specific area, notably: o the identification of new and promising countermeasures, o the potential of simple DAS for monitoring performance indicators over time, o the improvement of driver behaviour models for road transport simulation, o the possibilities for commercial applications of ND data; 5. Leaving behind the collected data to be used, subject to legal and ethical constraints, for additional analyses once UDRIVE is finished. During a 21-month data collection effort, UDRIVE will collect information on 210 vehicles, each for one year: 120 passenger cars, 50 trucks, and 40 powered two-wheelers. All data, including video data showing the forward view and the view of the driver as well as GIS data, will be collected continuously to enable knowledge in the various research areas to be brought well beyond the current state of the art. The UDRIVE consortium consists of 19 partners and represents a good balance between different EU regions and various stakeholders. The consortium also represents a good balance between expertise on the various research areas and expertise on huge data acquisition and storage.

Keywords: naturalistic driving,human behaviour,road safety,eco-driving,large scale research
Sensors Towards Advanced Monitoring and Control of Gas Turbine Engines (STARGATE)

Framework: FP7 — Cooperation
Programme: Transport (including Aeronautics)
Destination: Aeronautics and air transport
Action type: Collaborative project
Countries involved: United Kingdom,United Kingdom,Germany,France,Sweden,Germany,Belgium,Switzerland,United Kingdom,France,United Kingdom,United Kingdom,United Kingdom,Germany,United Kingdom
Call:  (FP7-AAT-2012-RTD-1, 2012)
Start date: 2012-11-01
End date: 2016-02-29
Duration (months): 40.0
Total project cost (EUR): 8007743.87
EU funding (EUR): 4999002.0
Participants: 16
Project status: CLOSED

The headline objective of this project is to develop a suite of advanced sensors, instrumentation and related systems in order to contribute to the development of the next generation of green and efficient gas turbine engines (AAT.2012.1.1-3&4). Sensors are a vital enabling technology for gas turbines and are critical to validation of design tools, new products, engine control, and health monitoring. The limitations of sensors in terms of survival temperature, accuracy, stability, and degradation limit where measurements are made during development and the operating ceiling of the gas turbine. Engines are run with safety margin in order to safeguard components against mechanical failure. Consequently, they are not run at their most optimal, which impacts overall efficiency. For example, a 10C uncertainty on turbine entry temperature changes the specific fuel consumption by 0.2%. Also a 0.2mm change in turbine tip clearance changes the specific fuel consumption by 0.4%. It is believed that with better sensing techniques, in excess of 500,000 tonnes of kerosene could be saved per annum, which equates to a CO2 saving of over 1.5 millions tonnes. Despite some successes in recent research, it has become clear that the capability gaps are not closing quickly enough. Further research in to sensors and instrumentation is, therefore, absolutely essential if the capability gaps are to be filled at an adequate rate. The STARGATE project intends to target these critical gaps and create the biggest impact possible within the constraints of the Call budget. The project will develop a range of advanced new sensors for high temperature gas path, surface, and structural measurements. The project also contains some detailed studies on wireless sensing. The sensors will be validated using both laboratory and rig trials to define their performance against specific targets. The project is being lead by Meggitt UK and includes 5 of the EU’s foremost gas turbine manufacturers.

Keywords: advanced sensors,instumentation,wireless,high temperature,gas turbines,efficiency,greening,monitoring,control,engine health management,acare 2020,co2 reduction
Integrated Design of Optimal Ventilation Systems for Low Cabin and Ramp Noise (IDEALVENT)

Framework: FP7 — Cooperation
Programme: Transport (including Aeronautics)
Destination: Aeronautics and air transport
Action type: Collaborative project
Countries involved: Belgium,Germany,Sweden,Belgium,France,France,Brazil,Russian Federation
Call:  (FP7-AAT-2012-RTD-1, 2012)
Start date: 2012-10-01
End date: 2016-09-30
Duration (months): 48.0
Total project cost (EUR): 3729596.0
EU funding (EUR): 2608271.0
Participants: 10
Project status: CLOSED

Reaching low levels of cabin and ramp noise is crucial to ensure the satisfaction of aircraft passengers and a safe working environment for the crew and personnel servicing the grounded aircraft. From the passenger and personnel standpoint, good thermal and acoustic comfort is important to minimize both stress symptoms and tiredness. Required to provide satisfactory air quality and temperature, the Environmental Control Systems (ECS) currently used are key contributors to the acoustic nuisance within the cabin and around the grounded aircraft. Reducing the amount of noise produced by the ECS will therefore have a direct impact on the passenger satisfaction and personnel health and safety. Unlike aircraft exterior noise, which has received considerable attention in past and currently running research projects, the noise emitted by confined flows in ECS assemblies involves complex mechanisms that haven’t been sufficiently investigated to permit the noise reduction wished by passengers and regulators. Acoustic and hydrodynamic interactions between subcomponents have so far been largely neglected despite being crucial. Thorough experimental studies will be conducted in order provide a deeper understanding of these mechanisms. A combination of accurate scale-resolved methods with low-CPU cost statistical/stochastic methods will then be proposed as an original modelling and design approach. Integrated passive flow and noise control strategies will be explored both experimentally and numerically. The knowledge gained in the experimental and numerical investigations of the installation effects will permit devising and optimise strategies having the best potential for reducing ECS noise. The best noise reduction strategies will be finally tested on a full-scale ECS system, and their impact towards improved passenger comfort and airport personnel health will be assessed with respect to the objectives of the Work Programme and relevant regulations.

Keywords: cabin noise,ramp noise,ventilation noise,aeroacoustic simulation,passive control