5 results on '"Dargent Lauren"'
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2. Ontology-based data integration in a distributed context of coalition air missions
- Author
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Ennaoui, Karima, Faivre, Mathieu, Hassan, Shahriar, Rey, Christophe, Dargent, Lauren, Girod, Hervé, Nguifo, Engelbert, Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Dassault Aviation, Rey, Christophe, and Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne)
- Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI] ,[INFO.INFO-LO] Computer Science [cs]/Logic in Computer Science [cs.LO] ,[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB] ,[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB] ,[INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO] ,[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] - Abstract
International audience; The IBC (Knowledge Base Integration) project addresses an issue of ontology-based data integration. It aims at combining data residing in different actors (aircraft, drone, satellite...) during an air mission scenario and providing users with a unified view of all available data, in a communication constrained environment. We describe the solution we have implemented based on mediation. We use rule languages to process queries using an OWL2 domain ontology and RDF triples to store data. We also give a performance analysis of our prototype.
- Published
- 2021
3. M[eye]cro
- Author
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Wambecke, Jérémy, primary, Goguey, Alix, additional, Nigay, Laurence, additional, Dargent, Lauren, additional, Hauret, Daniel, additional, Lafon, Stéphanie, additional, and de Visme, Jean-Samuel Louis, additional
- Published
- 2021
- Full Text
- View/download PDF
4. List of Contributors
- Author
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Nounagnon F. Agbangla, Atahan Agrali, Cédric T. Albinet, Awad Aljuaid, Guillaume Andéol, Jean M. André, Pietro Aricò, Branthomme Arnaud, Romain Artico, Michel Audiffren, Hasan Ayaz, Fabio Babiloni, Wendy Baccus, Carryl L. Baldwin, Hubert Banville, Klaus Bengler, Bruno Berberian, Jérémy Bergeron-Boucher, Ali Berkol, Pierre Besson, Siddharth Bhatt, Arianna Bichicchi, Martijn Bijlsma, Nikolai W.F. Bode, Vincent Bonnemains, Gianluca Borghini, Guillermo Borragán, Marc-André Bouchard, Angela Bovo, Eric Brangier, Anne-Marie Brouwer, Heinrich H. Bülthoff, Christopher Burns, Vincent Cabibel, Tuna E. Çakar, Daniel Callan, Aurélie Campagne, Travis Carlson, William D. Casebeer, Deniz Zengin Çelik, Cindy Chamberland, Caroline P.C. Chanel, Peter Chapman, Luc Chatty, Laurent Chaudron, Philippe Chevrel, Lewis L. Chuang, Caterina Cinel, Bernard Claverie, Antonia S. Conti, Yves Corson, Johnathan Crépeau, Adrian Curtin, Frédéric Dehais, Arnaud Delafontaine, Gaétane Deliens, Arnaud Delorme, Stefano I. Di Domenico, Gianluca Di Flumeri, Jean-Marc Diverrez, Manh-Cuong Do, Mengxi Dong, Andrew T. Duchowski, Anirban Dutta, Lydia Dyer, Sonia Em, Kate Ewing, Stephen Fairclough, Brian Falcone, Tiago H. Falk, Sara Feldman, Ying Xing Feng, Victor S. Finomore, Nina Flad, Alice Formwalt, Alexandra Fort, Paul Fourcade, Marc A. Fournier, Jérémy Frey, C. Gabaude, Olivier Gagey, Marc Garbey, Liliana Garcia, Thibault Gateau, Lukas Gehrke, Nancy Getchell, Evanthia Giagloglou, Christiane Glatz, Kimberly Goodyear, Robert J. Gougelet, Jonas Gouraud, Klaus Gramann, Dhruv Grewal, Carlos Guerrero-Mosquera, Céline Guillaume, Martin Hachet, Alain Hamaoui, Gabriella M. Hancock, Peter A. Hancock, Ahmad Fadzil M. Hani, Amanda E. Harwood, Mitsuhiro Hayashibe, Terry Heiman-Patterson, Girod Hervé, Maarten A.J. Hogervorst, Amy L. Holloway, Jean-Louis Honeine, Keum-Shik Hong, Klas Ihme, Kurtulus Izzetoglu, Meltem Izzetoglu, Philip L. Jackson, Christophe Jallais, Christian P. Janssen, Branislav Jeremic, Meike Jipp, Evelyn Jungnickel, Hélio Kadogami, Gozde Kara, Waldemar Karwowski, Quinn Kennedy, Theresa T. Kessler, Muhammad J. Khan, Rayyan A. Khan, Marius Klug, Amanda E. Kraft, Michael Krein, Ute Kreplin, Bartlomiej Kroczek, Lauens R. Krol, Frank Krueger, Ombeline Labaune, Daniel Lafond, Claudio Lantieri, Paola Lanzi, Amine Laouar, Dargent Lauren, Rachel Leproult, Véronique Lespinet-Najib, Ling-Yin Liang, Fabien Lotte, Ivan Macuzic, Nicolas Maille, Horia A Maior, S. Malin, Alexandre Marois, Franck Mars, Nicolas Martin, Nadine Matton, Magdalena Matyjek, Kevin McCarthy, Ryan McKendrick, Tom McWilliams, Bruce Mehler, Ranjana Mehta, Ranjana K. Mehta, Mathilde Menoret, Yoshihiro Miyake, Alexandre Moly, Rabia Murtza, Makii Muthalib, Mark Muthalib, Noman Naseer, Jordan Navarro, Roger Newport, Anton Nijholt, Michal Ociepka, Morellec Olivier, Ahmet Omurtag, Banu Onaral, Hiroki Ora, Bob Oudejans, Özgürol Öztürk, Martin Paczynski, Nico Pallamin, Raja Parasuraman, Mark Parent, René Patesson, Kou Paul, Philippe Peigneux, Matthias Peissner, G. Pepin, Stephane Perrey, Vsevolod Peysakhovich, Markus Plank, Riccardo Poli, Kathrin Pollmann, Simone Pozzi, Nancy M. Puccinelli, Jean Pylouster, Kerem Rızvanoğlu, Martin Ragot, Bryan Reimer, Emanuelle Reynaud, Joohyun Rhee, Jochem W. Rieger, Anthony J. Ries, Benoit Roberge-Vallières, Achala H. Rodrigo, Anne L. Roggeveen, Ricardo Ron-Angevin, Guillaume Roumy, Raphaëlle N. Roy, Anthony C. Ruocco, Bartlett A. Russell, Jon Russo, Richard M. Ryan, Amanda Sargent, Kelly Satterfield, Ben D. Sawyer, Sébastien Scannella, Menja Scheer, Melissa Scheldrup, Alex Schilder, Nicolina Sciaraffa, Lee Sciarini, Magdalena Senderecka, Sarah Sharples, Tyler H. Shaw, Patricia A. Shewokis, Andrea Simone, Hichem Slama, Alastair D. Smith, Bertille Somon, Hiba Souissi, Moritz Späth, Kimberly L. Stowers, Clara Suied, Junfeng Sun, Rajnesh Suri, Tong Boon Tang, Yingying Tang, Emre O. Tartan, Nadège Tebbache, Franck Techer, Cengiz Terzibas, Catherine Tessier, Claudine Teyssedre, Hayley Thair, Jean-Denis Thériault, Alexander Toet, Shanbao Tong, Jonathan Touryan, Amy Trask, Sébastien Tremblay, Anirudh Unni, François Vachon, Davide Valeriani, Benoît Valéry, Helma van den Berg, Valeria Vignali, Mathias Vukelić, Jijun Wang, Max L. Wilson, Emily Wusch, Petros Xanthopoulos, Eric Yiou, Amad Zafar, Thorsten O. Zander, Matthias D. Ziegler, and Ivana Živanovic-Macuzic
- Published
- 2019
- Full Text
- View/download PDF
5. Using Machine Learning Algorithms to Develop Adaptive Man–Machine Interfaces
- Author
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Kou Paul, Girod Herve, Branthomme Arnaud, Dargent Lauren, and Morellec Olivier
- Subjects
Computer science ,business.industry ,Crew ,ComputerApplications_COMPUTERSINOTHERSYSTEMS ,Context (language use) ,Cognition ,Workload ,Machine learning ,computer.software_genre ,Phase (combat) ,Automation ,Domain (software engineering) ,Variable (computer science) ,Artificial intelligence ,business ,Algorithm ,computer - Abstract
Automation has been introduced in aircraft cockpits to reduce pilot workload and increase safety. However, a number of reports mention “human factors” issues and misunderstandings of an automated-system behavior or its displays by the crew as major contributors leading to flight incidents. The interfaces should play, nevertheless, a crucial role in improving man–machine cooperation, by displaying “the right information at the right time.” This need of adapted displays and interfaces is more important than ever as the missions are becoming more and more complex, especially in the military domain. Moreover, many factors in workload mitigation are identified as crew or mission dependent and are highly variable from one flight to another, such as the cognitive demands of the current phase of flight or mission situation, the pilot's experience or “airmanship,” or individual physiological parameters. Thus, we can think of an adaptive intelligent interface that would monitor the automated system–pilot team as well as the mission operational context to provide the correct display and controls to the user and enable better cooperation between the human operator and the machine to match the current demands of the operational situation. This paper aims to investigate the potential of machine learning algorithms to develop these adaptive intelligent interfaces.
- Published
- 2018
- Full Text
- View/download PDF
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