Crushing properties of hexagonal adhesively bonded honeycombs loaded in their tubular direction

Aluminum hexagonal honeycombs loaded in their tubular direction have extremely good mechanical properties, including high stiffness to weight and energy absorption capacities. The corresponding load-displacement curve exhibits a long plateau accompanied by small fluctuations. These fluctuations are due to the propagation of a folding front through the studied sample, which is due to the creation of folds. This plateau load makes honeycombs the perfect candidates for use as energy-dissipative devices such as bumpers. Previous studies have largely focused on the study of the plateau load with less attention given to the length of the folds. However, it will be seen that this parameter is crucial for both the complete understanding of the mechanics of the folding and the derivation of the plateau load. We present first an introduction to the thematic of honeycomb. Then, the first model focuses precisely on the fold length. Two hypotheses are considered, a correlation between elastic buckling and folding first and a local propagation of the existing fold secondly. The second hypothesis is found to be correct, and the results are good for thin foils. For thick foils, a geometric limitation occurs, which makes the results less precise. Then, we are able to use the previous kinematics for the folding and derive a new set of formulas for the plateau load. The results are compared with experimental results and past formulas, and are found to be good, especially for thin foils, where our results for the fold length are more precise.M.S.Committee Chair: Mulalo Doyoyo; Committee Co-Chair: Reginald Desroches; Committee Member: Laurence J Jacob

Concept-based Summarization using Integer Linear Programming: From Concept Pruning to Multiple Optimal Solutions

International audienceIn concept-based summarization, sentence selection is modelled as a budgeted maximum coverage problem. As this problem is NP-hard, pruning low-weight concepts is required for the solver to find optimal solutions efficiently. This work shows that reducing the number of concepts in the model leads to lower Rouge scores, and more importantly to the presence of multiple optimal solutions. We address these issues by extending the model to provide a single optimal solution, and eliminate the need for concept pruning using an approximation algorithm that achieves comparable performance to exact inference

Evaluation of word embeddings against cognitive processes: primed reaction times in lexical decision and naming tasks

International audienceThis work presents a framework for word similarity evaluation grounded on cogni-tive sciences experimental data. Word pair similarities are compared to reaction times of subjects in large scale lexical decision and naming tasks under semantic priming. Results show that GloVe embeddings lead to significantly higher correlation with experimental measurements than other controlled and off-the-shelf embeddings, and that the choice of a training corpus is less important than that of the algorithm. Comparison of rankings with other datasets shows that the cognitive phenomenon covers more aspects than simply word related-ness or similarity

100ps time resolution with thin silicon pixel detectors and a SiGe HBT amplifier

A 100um thick silicon detector with 1mm2 pad readout optimized for sub-nanosecond time resolution has been developed and tested. Coupled to a purposely developed amplifier based on SiGe HBT technology, this detector was characterized at the H8 beam line at the CERN SPS. An excellent time resolution of (106+-1)ps for silicon detectors was measured with minimum ionizing particles

Robust Semantic Parsing with Adversarial Learning for Domain Generalization

International audienceThis paper addresses the issue of generalization for Semantic Parsing in an adversarial framework. Building models that are more robust to inter-document variability is crucial for the integration of Semantic Parsing technologies in real applications. The underlying question throughout this study is whether adversarial learning can be used to train models on a higher level of abstraction in order to increase their robustness to lexical and stylistic variations.We propose to perform Semantic Parsing with a domain classification adversarial task without explicit knowledge of the domain. The strategy is first evaluated on a French corpus of encyclopedic documents, annotated with FrameNet, in an information retrieval perspective, then on PropBank Semantic Role Labeling task on the CoNLL-2005 benchmark. We show that adversarial learning increases all models generalization capabilities both on in and out-of-domain data

Modèles génératif et discriminant en analyse syntaxique : expériences sur le corpus arboré de Paris 7

International audienceNous présentons une architecture pour l'analyse syntaxique en deux étapes. Dans un premier temps un analyseur syntagmatique construit, pour chaque phrase, une liste d'analyses qui sont converties en arbres de dépendances. Ces arbres sont ensuite réévalués par un réordonnanceur discriminant. Cette méthode permet de prendre en compte des informations auxquelles l'analyseur n'a pas accès, en particulier des annotations fonction- nelles. Nous validons notre approche par une évaluation sur le corpus arboré de Paris 7. La seconde étape permet d'améliorer significativement la qualité des analyses retournées, quelle que soit la métrique utilisée

A Framework for Information Accessibility in Large Video Repositories

International audienceOnline videos are a medium of choice for young adults to access or receive information, and recent work has highlighted that it is a particularly effective medium for adults with intellectual disability, by its visual nature. Reflecting on a case study presenting fieldwork observations of how adults with intellectual disability engage with videos on the Youtube platform, we propose a framework to define and evaluate the accessibility of such large video repositories, from an informational perspective. The proposed framework nuances the concept of information accessibility from that of the accessibility of information access interfaces themselves (generally catered for under web accessibility guidelines), or that of the documents (generally covered in general accessibility guidelines). It also includes a notion of search (or browsing) accessibility, which reflects the ability to reach the document containing the information. In the context of large information repositories, this concept goes beyond how the documents are organized into how automated processes (browsing or searching) can support users. In addition to the framework we also detail specifics of document accessibility for videos. The framework suggests a multi-dimensional approach to information accessibility evaluation which includes both cognitive and sensory aspects. This framework can serve as a basis for practitioners when designing video information repositories accessible to people with intellectual disability, and extends on the information presentation guidelines such as suggested by the WCAG. Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only

Leveraging study of robustness and portability of spoken language understanding systems across languages and domains: the PORTMEDIA corpora

International audienceThe PORTMEDIA project is intended to develop new corpora for the evaluation of spoken language understanding systems. The newly collected data are in the field of human-machine dialogue systems for tourist information in French in line with the MEDIA corpus. Transcriptions and semantic annotations, obtained by low-cost procedures, are provided to allow a thorough evaluation of the systems' capabilities in terms of robustness and portability across languages and domains. A new test set with some adaptation data is prepared for each case: in Italian as an example of a new language, for ticket reservation as an example of a new domain. Finally the work is complemented by the proposition of a new high level semantic annotation scheme well-suited to dialogue data

Sustainability of the chemical manufacturing industry - Towards a new paradigm?

This paper describes the current situation of the chemicalmanufacturingindustry, with special reference to Europe and looks to the future sustainability demands on the sector, and the implications of these demands for chemical engineering education. These implications include definitions of sustainability criteria for the sector and the need for transparent reporting under the Triple Bottom Line approach. The response of the education system to the sustainability agenda over the years and a number of strategies to incorporate it into courses are described. The important role of chemical (or more generally, process) engineers in delivering sustainable solutions is emphasised but this also suggests that anew way of thinking about the discipline is required. Indeed, this paper argues that the demand for a sustainable chemicalmanufacturing sector could bring about the next paradigm shift in the discipline which has been predicted for some time

Hyperuniform monocrystalline structures by spinodal solid-state dewetting

Materials featuring anomalous suppression of density fluctuations over large length scales are emerging systems known as disordered hyperuniform. The underlying hidden order renders them appealing for several applications, such as light management and topologically protected electronic states. These applications require scalable fabrication, which is hard to achieve with available top-down approaches. Theoretically, it is known that spinodal decomposition can lead to disordered hyperuniform architectures. Spontaneous formation of stable patterns could thus be a viable path for the bottom-up fabrication of these materials. Here we show that mono-crystalline semiconductor-based structures, in particular Si$_{1-x}$Ge$_{x}$ layers deposited on silicon-on-insulator substrates, can undergo spinodal solid-state dewetting featuring correlated disorder with an effective hyperuniform character. Nano- to micro-metric sized structures targeting specific morphologies and hyperuniform character can be obtained, proving the generality of the approach and paving the way for technological applications of disordered hyperuniform metamaterials. Phase-field simulations explain the underlying non-linear dynamics and the physical origin of the emerging patterns.Comment: 6 pages, 3 figures, supplementary information (7 pages) enclose