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31.
Coated plutonia particle fuel has been proposed recently for use in radioisotope power systems and radioisotope heater units for a variety of space missions requiring power levels from milliwatts to tens or even hundreds of watts. The 238PuO2 fuel kernels are coated with a strong layer of ZrC designed to fully retain the helium gas generated by the radioactive decay of 238Pu. A recent investigation has concluded that helium retention in large-grain (200 μm) granular and polycrystalline fuel kernels is possible even at high-temperatures (>1700 K). Results of performance analysis showed that this fuel form could increase by 2.3–2.4 times the thermal power output of a light weight radioisotope heater unit. These figures are for a single-size (500 μm) particles compact, assuming 10% and 5% helium gas release respectively, and a fuel temperature of 1723 K, following 10 years of storage. A binary-size (300 and 1200 μm) particles compact increases the thermal power output of the RHU by an additional 15%. 相似文献
32.
In this paper, we consider dynamical graph-based models, which are well fitted for the structural analysis of complex systems. A significant amount of work has been devoted to the controllability of such graph based models, e.g. recently for multi-agent systems or complex networks. We study here the controllability through input addition in this framework. We present several variants of this problem depending on the freedom which is left to the designer on the additional inputs. We use a unified framework, which allows us to encompass the different applications and representations (large scale systems, complex communications networks, multi-agent systems, …) and provide convenient graph tools for their analysis. Our contribution is to characterize the structural modifications of the system resulting from an input addition (or a leader selection) and of the mechanisms which lead to controllability. We provide information on the possible location of additional inputs and on the minimal number of inputs to be added for controllability. 相似文献
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35.
Caroline Privault Jacki O’Neill Victor Ciriza Jean-Michel Renders 《Artificial Intelligence and Law》2010,18(4):459-479
This paper describes a tool for assisting lawyers and paralegal teams during document review in eDiscovery. The tool combines
a machine learning technology (CategoriX) and advanced multi-touch interface capable of not only addressing the usual cost,
time and accuracy issues in document review, but also of facilitating the work of the review teams by capitalizing on the
intelligence of the reviewers and enabling collaborative work. 相似文献
36.
Morphology development during the synthesis at room temperature of an interpenetrating polyurethane/poly(methyl methacrylate) network was investigated by small-angle X-ray scattering in relation with their relative kinetics of formation, determined by Fourier transform infra red spectroscopy. When the time lag between the onset of the two reactions is short, macroscopic phase separation occurs as the polyurethane network is incompletely formed. However, when the time lag increases, the poly(methyl methacrylate) forms into a more continuous network which limits the growth of phase separation to a close environment. 相似文献
37.
Marcin Idczak Dominique Groleau Patrice Mestayer Jean-Michel Rosant Jean-François Sini 《Building and Environment》2010
This paper presents a validation of the thermo-radiative model SOLENE and its application for analysing the street canyon energy balance. The validation data were selected from the temperature and radiation measurements obtained during the JAPEX campaign, previously described by Idczak et al. [16]: a set of four lines of steel containers buildings composing three parallel street canyons at an approximate 1:5 scale. Reference weather data and micrometeorological conditions within the canyon were measured. Numerical simulations were carried out using the meteorological measurements as model inputs. The simulated surface temperatures and radiation fluxes are compared with the measurements for a full week period, with a focus on a day with clear sky conditions. The street canyon energy balance analysis demonstrates that the most energetic surface was the street ground due to its thick surface layer of tar-coated gravels while the walls had a low heat capacity. The thermal radiation balance was negative for all canyon surfaces. The sensible heat was transferred mainly from the canyon surfaces to the ambient air, but also from the air to the ground in the morning. The effective albedo of the canyon had a diurnal value of 0.20–0.25, but dropped to 0.10 in the afternoon when the ground strongly transformed the direct and reflected solar radiation into sensible heat. This narrow street configuration enhanced solar radiation absorption and longwave radiation trapping. 相似文献
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39.
Julien Ah-Pine Marco Bressan Stephane Clinchant Gabriela Csurka Yves Hoppenot Jean-Michel Renders 《Multimedia Tools and Applications》2009,42(1):31-56
This paper deals with multimedia information access. We propose two new approaches for hybrid text-image information processing
that can be straightforwardly generalized to the more general multimodal scenario. Both approaches fall in the trans-media
pseudo-relevance feedback category. Our first method proposes using a mixture model of the aggregate components, considering
them as a single relevance concept. In our second approach, we define trans-media similarities as an aggregation of monomodal
similarities between the elements of the aggregate and the new multimodal object. We also introduce the monomodal similarity
measures for text and images that serve as basic components for both proposed trans-media similarities. We show how one can
frame a large variety of problem in order to address them with the proposed techniques: image annotation or captioning, text
illustration and multimedia retrieval and clustering. Finally, we present how these methods can be integrated in two applications:
a travel blog assistant system and a tool for browsing the Wikipedia taking into account the multimedia nature of its content.
Dr. Julien Ah-Pine joined the XRCE Grenoble as Research Engineer in 2007. He is part of the Textual and Visual Pattern Analysis group and his current research activities are related to multi-modal information retrieval and machine learning. He received his PhD degree in mathematics from Pierre and Marie Curie University (University of Paris 6). From 2003 to 2007, he was with Thales Communications, working on relational analysis, data and text mining methods and social choice theory. Dr. Marco Bressan is Area Manager of the Textual and Visual Pattern Analysis area at Xerox Research Centre Europe. His main research interests are statistical learning and classification; image and video semantic scene understanding; image enhancement and aesthetics; object detection and recognition, particularly when dealing with uncontrolled environments. Prior to Xerox, several of his contributions in these fields were applied to a variety of scenarios including biometric solutions, data mining, CBIR and industrial vision. Dr. Bressan holds a BA in Applied Mathematics from the University of Buenos Aires, a M.Sc. in Computer Vision from the Computer Vision Centre in Spain and a Ph.D. in Computer Science and Artificial Intelligence from the Autonomous University of Barcelona. He is an active member of the network of Argentinean researchers abroad and one of the founders of the network of computer vision and cognitive science researchers. Stephane Clinchant is Ph.D. Student at University Joseph Fourier (Grenoble, France) and at the Xerox Research Centre Europe, that he joined in 2005. Before joining XRCE, Stephane obtained a Master Degree in Computer Sciences in 2005 from the Ecole Nationale Superieure d’Electrotechnique, d’Informatique, d’Hydraulique et des Telecommunications (France). His current research interests mainly focus on Machine Learning for Natural Language Processing and Multimedia Information Access. Dr. Gabriela Csurka is a research scientist in the Textual and Visual Pattern Analysis team at Xerox Research Centre Europe (XRCE). She obtained her Ph.D. degree (1996) in Computer Science from University of Nice Sophia - Antipolis. Before joining XRCE in 2002, she worked in fields such as stereo vision and projective reconstruction at INRIA (Sophia Antipolis, Rhone Alpes and IRISA) and image and video watermarking at University of Geneva and Institute Eurécom, Sophia Antipolis. Author of several publications in main journals and international conferences, she is also an active reviewer both for journals and conferences. Her current research interest concerns the exploration of new technologies for image content and aesthetic analysis, cross-modal image categorization and semantic based image segmentation. Yves Hoppenot is in charge of the development and integration of new technologies in our European research Technology Showroom. He is a software expert for the production, office and services sectors. Yves joined the Xerox Research Centre Europe in 2001. He graduated from the Ecole National Superieure des Telecommunications, Brest in France, and received a Master of Science degree from the Tampere University of Technology in Finland. Dr. Jean-Michel Renders joined the XRCE Grenoble as Research Engineer in 2001. His current research interests mainly focus on Machine Learning techniques applied to Statistical Natural Language Processing and Text Mining. Before joining XRCE, Jean-Michel obtained a PhD in Applied Sciences from the University of Brussels in 1993. He started his research activities in 1988, in the field of Robotics Dynamics and Control. Then, he joined the Joint Research Center of the European Communities to work on biologial metaphors (Genetic Algorithms, Neural Networks and Immune Networks) applied to process control. After spending one year as Visiting Scientist at York University (England), he spent 4 years applying Artificial Intelligence and Machine Learning Techniques in Industry (Tractebel - Suez). Then, he worked as Data Mining Senior Consultant and led projects in most major Belgian banks and utilities. 相似文献
Gabriela CsurkaEmail: |
Dr. Julien Ah-Pine joined the XRCE Grenoble as Research Engineer in 2007. He is part of the Textual and Visual Pattern Analysis group and his current research activities are related to multi-modal information retrieval and machine learning. He received his PhD degree in mathematics from Pierre and Marie Curie University (University of Paris 6). From 2003 to 2007, he was with Thales Communications, working on relational analysis, data and text mining methods and social choice theory. Dr. Marco Bressan is Area Manager of the Textual and Visual Pattern Analysis area at Xerox Research Centre Europe. His main research interests are statistical learning and classification; image and video semantic scene understanding; image enhancement and aesthetics; object detection and recognition, particularly when dealing with uncontrolled environments. Prior to Xerox, several of his contributions in these fields were applied to a variety of scenarios including biometric solutions, data mining, CBIR and industrial vision. Dr. Bressan holds a BA in Applied Mathematics from the University of Buenos Aires, a M.Sc. in Computer Vision from the Computer Vision Centre in Spain and a Ph.D. in Computer Science and Artificial Intelligence from the Autonomous University of Barcelona. He is an active member of the network of Argentinean researchers abroad and one of the founders of the network of computer vision and cognitive science researchers. Stephane Clinchant is Ph.D. Student at University Joseph Fourier (Grenoble, France) and at the Xerox Research Centre Europe, that he joined in 2005. Before joining XRCE, Stephane obtained a Master Degree in Computer Sciences in 2005 from the Ecole Nationale Superieure d’Electrotechnique, d’Informatique, d’Hydraulique et des Telecommunications (France). His current research interests mainly focus on Machine Learning for Natural Language Processing and Multimedia Information Access. Dr. Gabriela Csurka is a research scientist in the Textual and Visual Pattern Analysis team at Xerox Research Centre Europe (XRCE). She obtained her Ph.D. degree (1996) in Computer Science from University of Nice Sophia - Antipolis. Before joining XRCE in 2002, she worked in fields such as stereo vision and projective reconstruction at INRIA (Sophia Antipolis, Rhone Alpes and IRISA) and image and video watermarking at University of Geneva and Institute Eurécom, Sophia Antipolis. Author of several publications in main journals and international conferences, she is also an active reviewer both for journals and conferences. Her current research interest concerns the exploration of new technologies for image content and aesthetic analysis, cross-modal image categorization and semantic based image segmentation. Yves Hoppenot is in charge of the development and integration of new technologies in our European research Technology Showroom. He is a software expert for the production, office and services sectors. Yves joined the Xerox Research Centre Europe in 2001. He graduated from the Ecole National Superieure des Telecommunications, Brest in France, and received a Master of Science degree from the Tampere University of Technology in Finland. Dr. Jean-Michel Renders joined the XRCE Grenoble as Research Engineer in 2001. His current research interests mainly focus on Machine Learning techniques applied to Statistical Natural Language Processing and Text Mining. Before joining XRCE, Jean-Michel obtained a PhD in Applied Sciences from the University of Brussels in 1993. He started his research activities in 1988, in the field of Robotics Dynamics and Control. Then, he joined the Joint Research Center of the European Communities to work on biologial metaphors (Genetic Algorithms, Neural Networks and Immune Networks) applied to process control. After spending one year as Visiting Scientist at York University (England), he spent 4 years applying Artificial Intelligence and Machine Learning Techniques in Industry (Tractebel - Suez). Then, he worked as Data Mining Senior Consultant and led projects in most major Belgian banks and utilities. 相似文献
40.
François Treussart Nicolas Dubreuil Jongthan Cave Knight Vahid Sandoghdar Jean Hare Valçrie Lefçvre-Seguin Jean-Michel Raimond Serge Haroche 《电信纪事》1997,52(11-12):557-568
Light can be confined efficiently in the high-Q, small-volume whispering-gallery-modes observed in silica microspheres. By coupling these microspheres to eroded optical fibers and fiber tips, direct mapping of the whispering-gallery modes has been achieved and the mode numbers have been assessed. The properties of these modes have allowed us to obtain laser action with very low thresholds in Nd-doped silica microspheres. Further projects in the field of non-linear optics and cavity quantum electrodynamics are described. 相似文献