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Coherence of the digital twins for the industry of the future: Modeling, visualization and interaction with 4D digital mockups coupled with physical systems – COHERENCE4D
Introduced at the beginning of the century by NASA, the concept of the digital twin is now at the heart of digitalization issues and appears to be an essential element for meeting the challenges of the fourth industrial revolution. The digital twin is a dynamic virtual representation that can follow
Collaborative Agile Miniaturized Robotics for ultra-precise assembly – COLAMIR
Benefiting from increased flexibility compared to industrial machines, robotics has taken a prominent place in the manufacturing industry, thus reducing the cost of production diversification. Today, however, the low rate of robotization in French SMEs should challenge the robotics community, partic
Collaborative Continuity from Digital to Human
The CONTINUUM project will create a collaborative research infrastructure of 30 platforms located throughout France, to advance interdisciplinary research based on interaction between computer science and the human and social sciences. Thanks to CONTINUUM, 37 research teams will develop cutting-edge
Collecting, Representing, cOmpleting, merging and Querying heterogeneous and UncertaIn waStewater and stormwater network data – CROQUIS
Public and private stakeholders of the wastewater and stormwater sectors are increasingly confronted with the analysis of massive heterogeneous data (imprecise and uncertain geographical data, digital/analogue maps, etc). Obtaining accurate and updated information on the underground wastewater netwo
Combinatorial development of efficient thermoelectric half-Heusler materials using machine learning, DFT and experiments – CombiHeusler
The demand for green energy has constantly risen with increasing energy consumption and the impending climate change. This is exacerbated by unabated fossil fuel depletion whereas 60% of primary energy is wasted as unused heat. Thermoelectric (TE) materials are a viable green energy alternative as t
Combining AI and MC Simulations for Real-Time Quantification of DNA Damage Response to Ionizing Radiation – ARSINOE
The ARSINOE project represents a significant advancement in the field of radiation therapy planning, leveraging artificial intelligence (AI) to optimize the treatment process. By integrating AI into Monte Carlo (MC) simulations, ARSINOE aims to predict the biological consequences of ionizing radiati
Combining Artificial Intelligence learning with WEARable devices for improved stress diagnostics – AI-Wear
Wearable Biometric Monitoring Devices (WBMDs) represent a recent alterative for the collection of health-related data from people. WBMDs allow for continuous and real time data collection in natural settings. However, these devices face two key challenges: 1) WBMDs require seamless interfaces that a
Combining Machine Learning and Automated Planning Methods for Robust Heterogeneous Robot Teams – PARHéRo
The PARHéRo project explicitly aims to increment synergies between scientific and industrial research to anticipate and control the evolution of heterogeneous robotic platforms in complex, unknown and/or hostile environments. The successful completion of robotic missions is ensured by the high degre
Combining artificial intelligence and environmental DNA to predict marine fish range shifts under global change – SHIFTeDNA
Atmospheric and oceanic warming is currently accelerating at an unprecedented rate, with consequences for biodiversity as the modification of species geographic distribution, hereafter range shift. Fish, as marine ectotherms, are particularly sensitive to these temperature changes. These modificatio
