Fingerprinting stress: stylolite and calcite twinning paleopiezometry revealing the complexity of progressive stress patterns during folding-the case of the Monte Nero anticline in the Apennines, Italy

In this study we show for the first time how quantitative stress estimates can be derived by combining calcite twinning and stylolite roughness stress fingerprinting techniques in a fold-and-thrust belt. First, we present a new method that gives access to stress inversion using tectonic stylolites without access to the stylolite surface and compare results with calcite twin inversion. Second, we use our new approach to present a high-resolution deformation and stress history that affected Meso-Cenozoic limestone strata in the Monte Nero Anticline during its late Miocene-Pliocene growth in the Umbria-Marche Arcuate Ridge (northern Apennines, Italy). In this area an extensive stylolite-joint/vein network developed during layer-parallel shortening (LPS), as well as during and after folding. Stress fingerprinting illustrates how stress in the sedimentary strata did build up prior to folding during LPS. The stress regime oscillated between strike slip and compressional during LPS before ultimately becoming strike slip again during late stage fold tightening. Our case study shows that high-resolution stress fingerprinting is possible and that this novel method can be used to unravel temporal relationships that relate to local variations of regional orogenic stresses. Beyond regional implications, this study validates our approach as a new powerful toolbox to high-resolution stress fingerprinting in basins and orogens combining joint and vein analysis with sedimentary and tectonic stylolite and calcite twin inversion techniques

Uniaxial compression of calcite single crystals at room temperature: insights into twinning activation and development

E-twinning is a common plastic deformation mechanism in calcite deformed at low temperature. Strain rate, temperature and confining pressure have negligible effects on twinning activation which is mainly dependent on differential stress. The critical resolved shear stress (CRSS) required for twinning activation is dependent on grain size and strain hardening. This CRSS value may obey the Hall–Petch relation, but due to sparse experimental data its actual evolution with grain size and strain still remains a matter of debate. In order to provide additional constraints on twinning activation and development, new mechanical tests were carried out at room temperature on unconfined single crystals of calcite, with different sizes and crystallographic orientations. Uniaxial deformation was performed at a controlled displacement rate, while the sample surface was monitored using optical microscopy and a high-resolution CCD (charge-coupled device) camera. The retrieved macroscopic stress–strain behavior of the crystals was correlated with the surface observations of the deformation process. Results show (1) the onset of crystal plasticity with the activation of the first isolated mechanical twins during the strain hardening stage, and (2) the densification and thickening of twin lamellae during the steady-state flow stress stage. Such thickening of twin lamellae at room temperature emphasizes that calcite twin morphology is not controlled solely by temperature. The different values for the CRSS obtained for the activation of isolated twins and for the onset of twin densification and thickening raises questions regarding the appropriate value to be considered when using calcite twin data for stress inversion purposes.</p

A novel multidimensional model for the OLAP on documents : modeling, generation and implementation

International audienceAs the amount of textual information grows explosively in various kinds of business systems, it becomes more and more essential to analyze both structured data and unstructured textual data simultaneously. However information contained in non structured data (documents and so on) is only partially used in business intelligence (BI). Indeed On-Line Analytical Processing (OLAP) cubes which are the main support of BI analysis in decision support systems have focused on structured data. This is the reason why OLAP is being extended to unstructured textual data. In this paper we introduce the innovative “Diamond” multidimensional model that will serve as a basis for semantic OLAP on XML documents and then we describe the meta modeling, generation and implementation of a the Diamond multidimensional model

Une approche par dissimilarité pour la caractérisation de jeux de données

La caractérisation de jeu de données reste un verrou majeur de l'analyse de données intelligente. Une majorité d'approches à ce problème agrègent les informations décrivant les attributs individuels des jeux de données, ce qui représente une perte d'information. Nous proposons une approche par dissimilarité permettant d'éviter cette agrégation, et étudions son intérêt dans la caractérisation des performances d'algorithmes de classifications, et dans la résolution de problèmes de méta-apprentissage

Modèle multidimensionnel en diamant dédié à l'OLAP sémantique de documents

National audienceLe document électronique représente aujourd’hui un support d’information que les entreprises ne peuvent plus négliger si elles veulent être certaines d’identifier et de gérer toutes les données qui leur sont utiles au quotidien. Plusieurs travaux ont proposé l’application des techniques OLAP (« On-line Analytical Processing ») aux informations documentaires. Dans cet article, nous présentons un nouveau modèle multidimensionnel dédié à l’OLAP de documents. Ce modèle, dit en diamant, est organisé autour d’une dimension centrale qui traduit la sémantique du contenu textuel du document

Diamond multidimensional model and aggregation operators for document OLAP

International audienceOn-Line Analytical Processing (OLAP) has generated methodologies for the analysis of structured data. However, they are not appropriate to handle document content analysis. Because of the fast growing of this type of data, there is a need for new approaches abling to manage textual content of data. Generally, these data exist in XML format. In this context, we propose an approach of construction of our Diamond multidimensional model, which includes semantic dimension to better consider the semantics of textual data In addition, we propose new aggregation operators for textual data in OLAP environment

Caractérisation d'instances d'apprentissage pour méta-mining évolutionnaire.

Les nombreuses techniques d'apprentissage et de fouille de données mises au point au cours des dernières décennies peuvent se révéler d'importants atouts dans divers domaines, mais choisir la technique la plus appropriée pour une application précise est une tâche très complexe pour un non-expert. Notre objectif est ainsi de produire un assistant de modélisation répondant à ce besoin, par une approche à la frontière du méta-apprentissage et des heuristiques évolutionnaires. Nous présentons ici le fonctionnement prévu de cet assistant, suivi d'une discussion de notre approche du problème de caractérisation des instances d'apprentissage, qui reste un verrou majeur du méta-apprentissage et méta-mining

Segmentation Parole/Musique pour la transcription automatique

Colloque avec actes et comité de lecture. internationale.International audienceDans cet article nous présentons une étude sur l'utilisation des paramètres MFCC dans la tâche de segmentation parole/musique indispensable dans les applications de transcription automatique d'émissions radiophoniques. Nous avons étudié, l'influence du nombre de coefficients MFCC, celle des paramètres dynamiques et notamment celui de la variance des coefficients MFCC calculée sur une seconde. Les tests ont été effectués sur un corpus radiophonique réel et difficile et sur le corpus de Scheirer. || The speech/music segmentation process is very useful as a first step for different tasks like speech recognition or automatic transcription. In this article, we present some studies about the use of MFCC for this speech/music segmentation. We mainly use a realworld broadcast corpus with various backgrounds and superimposed segments (speech with music). We investigate the role of the number of cepstral coefficients, the influence of different kinds of dynamic parameters, and the robustness of some of them when a mismatch between train and test conditions occurs. So we can notice that the standard MFCC coefficients with the first and second derivatives achieve good results. But, better performances were obtained with dynamic parameters and mainly with the variance of the static coefficients computed on a longterm window (1s)

Audio Indexing on the Web: a Preliminary Study of Some Audio Descriptors

Colloque avec actes et comité de lecture. internationale.International audienceThe "Invisible Web" is composed of documents which can not be currently accessed by Web search engines, because they have a dynamic URL or are not textual, like video or audio documents. For audio documents, one solution is automatic indexing. It consists in finding good descriptors of audio documents which can be used as indexes for archiving and search. This paper presents an overview and recent results of the RAIVES project, a French research project on audio indexing. We present speech/music segmentation, speaker tracking, and keywords detection. We also give a few perspectives of the RAIVES project

Addressing the Meta-Learning problem with Metaheuristics

The many machine learning and data mining techniques produced over the last decades can prove invaluable assets in diverse fields, but choosing the most appropriate for a given application may be very difficult for a non-expert. Our objective is thus to provide modelling assistance using a meta-learning approach based on an evolutionary metaheuristic. We present the intended workflow of such modelling assistant and the expected challenges along our line of work