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1.
The aim of this study was to examine the reliability and validity of a French version of the Revised Children's Manifest Anxiety Scale (RCMAS). A sample of 2,666 school-age French-Canadian children completed the questionnaire. With regard to factor structure, the 5-factor model found in U.S. normative samples was confirmed. The internal consistency of the 5 scales and of the 2 global scales was good to excellent. Test-retest reliabilities after a 6-month period were also similar to those of the original version. Finally, the concurrent validity, assessed by a correlation with the State-Trait Anxiety Inventory for Children, was also found to be good. Results of the present study show that the French version of the RCMAS is a good instrument to assess anxiety in children. (PsycINFO Database Record (c) 2010 APA, all rights reserved)  相似文献   
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The paper reports the results of on-site regeneration catalytic bed of the natural gas reformer in a 5 kW PEM fuel cell system. The Ni catalyst previously poisoned by sulphur from the available natural gas, could be re-activated by injection of pure water steam, following the method developed for industrial reformers using the same metal catalyst: this method was shown to be perfectly efficient, provided no natural gas was fed during the operation. Results of the tests conducted are presented and discussed in relation to published data on S-sorption on Ni surfaces.  相似文献   
4.
A new cryogenic instrument was designed for the trapping of aerosols such as cigarette mainstream smoke at low temperature. The technique enabled the trapping of the mainstream smoke of a single cigarette and the particulate and vapor phases were trapped simultaneously. 2R4F reference cigarettes were smoked under International Standard Organization (ISO) regime and trapped at low temperature using the cryogenic instrument. After trapping, the mainstream smoke of the 2R4F reference cigarette was diluted with a solvent and selected smoke components could be quantified using gas-mass spectrometry (GCMS) and high-performance liquid chromatography (HPLC). The capability of the instrument for trapping the mainstream smoke was demonstrated. The feasibility of the procedure for the detection and the quantification of a large range of smoke components including carbonyls, alkaloids and organic volatile compounds (VOC) in the mainstream of a single cigarette was also shown.  相似文献   
5.
We perform continuous collision detection (CCD) for articulated bodies where motion is governed by an adaptive dynamics simulation. Our algorithm is based on a novel hierarchical set of transforms that represent the kinematics of an articulated body recursively, as described by an assembly tree. The performance of our CCD algorithm significantly improves as the number of active degrees of freedom in the simulation decreases.  相似文献   
6.
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.
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   
7.
Microsystem Technologies - This study presents the results on the feasibility of a resonant planar chemical capacitive sensor in the microwave frequency range suitable for gas detection and...  相似文献   
8.
We propose a self-stabilizing algorithm for constructing a Minimum Degree Spanning Tree (MDST) in undirected networks. Starting from an arbitrary state, our algorithm is guaranteed to converge to a legitimate state describing a spanning tree whose maximum node degree is at most Δ+1, where Δ is the minimum possible maximum degree of a spanning tree of the network.To the best of our knowledge, our algorithm is the first self-stabilizing solution for the construction of a minimum degree spanning tree in undirected graphs. The algorithm uses only local communications (nodes interact only with the neighbors at one hop distance). Moreover, the algorithm is designed to work in any asynchronous message passing network with reliable FIFO channels. Additionally, we use a fine grained atomicity model (i.e., the send/receive atomicity). The time complexity of our solution is O(mn2logn) where m is the number of edges and n is the number of nodes. The memory complexity is O(δlogn) in the send-receive atomicity model (δ is the maximal degree of the network).  相似文献   
9.
To maintain and understand large applications, it is important to know their architecture. The first problem is that unlike classes and packages, architecture is not explicitly represented in the code. The second problem is that successful applications evolve over time, so their architecture inevitably drifts. Reconstructing the architecture and checking whether it is still valid is therefore an important aid. While there is a plethora of approaches and techniques supporting architecture reconstruction, there is no comprehensive software architecture reconstruction state of the art and it is often difficult to compare the approaches. This paper presents a state of the art in software architecture reconstruction approaches.  相似文献   
10.
Changing behaviours and attitudes towards more sustainable individual energy consumption is a difficult topic to address. After identifying the most recurrent factors influencing the bad energy consumption, society's environmental short-sightedness, a lack of individual responsibility and a tendency to put responsibility upon firms, institutions, and governments, the authors evaluated the effect that business practices can have on individual behaviour. By qualifying as highly credible sources of information, positioning themselves as examples to follow, and providing its employees with the necessary smart and innovative technology, business communities can have a major impact on changing individual behaviours towards more sustainable energy consumption.  相似文献   
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