Modelling, simulation and characterization of epithelial cell culture biochip

A microfluidic Organ-on-Chip has been developed for monitoring the epithelial cells monolayer. Equivalent circuit Model was used to determine the electrical properties from the impedance spectra of the epithelial cells monolayer. Black platinum on platinum electrodes was electrochemically deposited onto the surface of electrodes to reduce the influence of the electrical double layer on the impedance measurements. Measurements of impedance with an Impedance Analyzer were done to validate the equivalent circuit model and the decrease of the double layer effect. A Lock-in Amplifier was designed to measure the impedance

Strategies for Contiguous Multiword Expression Analysis and Dependency Parsing

International audienceIn this paper, we investigate various strategies to predict both syntactic dependency parsing and contiguous multiword expression (MWE) recognition, testing them on the dependency version of French Treebank \cite{abeille:04}, as instantiated in the SPMRL Shared Task \cite{spmrl:st:2013}. Our work focuses on using an alternative representation of syntactically regular MWEs, which captures their syntactic internal structure. We obtain a system with comparable performance to that of previous works on this dataset, but which predicts both syntactic dependencies and the internal structure of MWEs. This can be useful for capturing the various degrees of semantic compositionality of MWEs

Expériences d'analyse syntaxique statistique du français

National audienceWe show that we can acquire satisfactory parsing results for French from data induced from the French Treebank using an unlexicalised parsing algorithm, that learns a probabilistic contex-free grammar with latent annotations. We investigate various instantiations of the treebank, in order to improve the performance of the learnt parser.Nous montrons qu'il est possible d'obtenir une analyse syntaxique statistique satisfaisante pour le français sur du corpus journalistique, à partir des données issues du French Treebank du laboratoire LLF, à l'aide d'un algorithme d'analyse non lexicalisé

Improving generative statistical parsing with semi-supervised word clustering

short paper (4 pages)International audienceWe present a semi-supervised method to improve statistical parsing performance. We focus on the well-known problem of lexical data sparseness and present experiments of word clustering prior to parsing. We use a combination of lexicon-aided morphological clustering that preserves tagging ambiguity, and unsupervised word clustering, trained on a large unannotated corpus. We apply these clusterings to the French Treebank, and we train a parser with the PCFG-LA unlexicalized algorithm of Petrov et al. (2006). We find a gain in French parsing performance: from a baseline of F1=86.76% to F1=87.37% using morphological clustering, and up to F1=88.29% using further unsupervised clustering. This is the best known score for French probabilistic parsing. These preliminary results are encouraging for statistically parsing morphologically rich languages, and languages with small amount of annotated data

Revelations of Folies through Geometric Transformations

This article presents an activity carried out in a course on representation in a master’s degree in architecture, which aims to train students in the practice and theory of geometric transformation for the production of shapes, using a case study from contemporary architectural design: the Folies of the Parc de la Villette

Lemmatization and lexicalized statistical parsing of morphologically rich languages: the case of French

This paper shows that training a lexicalized parser on a lemmatized morphologically-rich treebank such as the French Treebank slightly improves parsing results. We also show that lemmatizing a similar in size subset of the English Penn Treebank has almost no effect on parsing performance with gold lemmas and leads to a small drop of performance when automatically assigned lemmas and POS tags are used. This highlights two facts: (i) lemmatization helps to reduce lexicon data-sparseness issues for French, (ii) it also makes the parsing process sensitive to correct assignment of POS tags to unknown words

Le corpus Sequoia : annotation syntaxique et exploitation pour l'adaptation d'analyseur par pont lexical

National audienceWe present the building methodology and the properties of the Sequoia treebank, a freely available French corpus annotated following the French Treebank guidelines (Abeillé et Barrier, 2004). The Sequoia treebank comprises 3204 sentences (69246 tokens), from the French Europarl, the regional newspaper L'Est Républicain, the French Wikipedia and documents from the European Medicines Agency. We then provide a method for parser domain adaptation, that makes use of unsupervised word clusters. The method improves parsing performance on target domains (the domains of the Sequoia corpus), without degrading performance on source domain (the French treenbank test set), contrary to other domain adaptation techniques such as self-training.Nous présentons dans cet article la méthodologie de constitution et les caractéristiques du corpus Sequoia, un corpus en français, syntaxiquement annoté d'après un schéma d'annotation très proche de celui du French Treebank (Abeillé et Barrier, 2004), et librement disponible, en constituants et en dépendances. Le corpus comporte des phrases de quatre origines : Europarl français, le journal l'Est Républicain, Wikipédia Fr et des documents de l'Agence Européenne du Médicament, pour un total de 3204 phrases et 69246 tokens. En outre, nous présentons une application de ce corpus : l'évaluation d'une technique d'adaptation d'analyseurs syntaxiques probabilistes à des domaines et/ou genres autres que ceux du corpus sur lequel ces analyseurs sont entraînés. Cette technique utilise des clusters de mots obtenus d'abord par regroupement morphologique à l'aide d'un lexique, puis par regroupement non supervisé, et permet une nette amélioration de l'analyse des domaines cibles (le corpus Sequoia), tout en préservant le même niveau de performance sur le domaine source (le FTB), ce qui fournit un analyseur multi-domaines, à la différence d'autres techniques d'adaptation comme le self-training

Introduction to the special issue on annotated corpora

International audienceLes corpus annotés sont toujours plus cruciaux, aussi bien pour la recherche scien- tifique en linguistique que le traitement automatique des langues. Ce numéro spécial passe brièvement en revue l’évolution du domaine et souligne les défis à relever en restant dans le cadre actuel d’annotations utilisant des catégories analytiques, ainsi que ceux remettant en question le cadre lui-même. Il présente trois articles, l’un concernant l’évaluation de la qualité d’annotation, et deux concernant des corpus arborés du français, l’un traitant du plus ancien projet de corpus arboré du français, le French Treebank, le second concernant la conversion de corpus français dans le schéma interlingue des Universal Dependencies, offrant ainsi une illustration de l’histoire du développement des corpus arborés.Annotated corpora are increasingly important for linguistic scholarship, science and technology. This special issue briefly surveys the development of the field and points to challenges within the current framework of annotation using analytical categories as well as challenges to the framework itself. It presents three articles, one concerning the evaluation of the quality of annotation, and two concerning French treebanks, one dealing with the oldest project for French, the French Treebank, the second concerning the conversion of French corpora into the cross-lingual framework of Universal Dependencies, thus offering an illustration of the history of treebank development worldwide