Tesserae: A Search Engine for Allusion

The Tesserae Project is an interdisciplinary research effort employing computational methods to detect and analyze literary allusion (a form of text reuse) currently focusing on Latin and ancient Greek. The Project seeks funding to create a fully-functional, publicly available tool to detect similar phrases in two texts at rates that approach those of literary commentators. To this end, funding will support adding sensitivity to word meaning, phrase context, and sound similarity. Detection rate improvements will be measured against a set of 3000 parallel phrases previously graded for literary significance. A revised website will inform researchers of research results and new functions of the tool. The project team will give presentations and produce publications explaining the function, results, and theoretical consequences of the fully operational tool. This work is preliminary to an out-year Implementation Phase that will see the addition of English, French, Italian, and Spanish

Modeling the Role of Polysemy in Verb Categorization

Recent work has indicated that static word embeddings can predict human semantic categories (Majewska et al. 2021). In this paper, we consider the role of polysemy in semantic categorization, by comparing sense-level embeddings with previously studied static embeddings in their prediction of human-produced categories. We find that the polysemy is crucial for predicting human categories; sense-level embeddings dramatically outperform static embeddings in predicting semantic categories. Our findings highlight the role of polysemy in semantic categorization that is exclusively based on linguistic input

Virtual Super Resolution of Scale Invariant Textured Images Using Multifractal Stochastic Processes

International audienceWe present a new method of magnification for textured images featuring scale invariance properties. This work is originally motivated by an application to astronomical images. One goal is to propose a method to quantitatively predict statistical and visual properties of images taken by a forthcoming higher resolution telescope from older images at lower resolution. This is done by performing a virtual super resolution using a family of scale invariant stochastic processes, namely compound Poisson cascades, and fractional integration. The procedure preserves the visual aspect as well as the statistical properties of the initial image. An augmentation of information is performed by locally adding random small scale details below the initial pixel size. This extrapolation procedure yields a potentially infinite number of magnified versions of an image. It allows for large magnification factors (virtually infinite) and is physically conservative: zooming out to the initial resolution yields the initial image back. The (virtually) super resolved images can be used to predict the quality of future observations as well as to develop and test compression or denoising techniques

Amélioration virtuelle de la résolution d'images du Soleil par augmentation d'information invariante d'échelle

4 pagesNational audienceCurrent images of the quiet Sun from the spatial telescope EIT are such that 1 pixel = (1800km)2 whereas the smallest physical scales would be of about 100 m. The design of a high resolution spatial telescope where 1 pixel = (80 km)2 is planned. With a resolution 25 times finer, the images may be under-exposed or even useless. The point is to predict at best the quality of these images from the current observations. We exploit the scale invariance properties of images currently available to suggest a method to artificially improve (of a potentially infinite factor) the current images resolution by integrating details from a multifractal stochastic model. Quiet Sun images are magnified by a factor 32 while preserving the multiscale properties (spectrum, multiscaling) and assuring that reducing the magnified image gives the initial image back. We deduce from that an extrapolation of histograms of high resolution images allowing a prediction of the quality of images from a future high resolution telescope

Semantic Unity and Constructional Particularity: The French Se Faire Construction

Proceedings of the Eighteenth Annual Meeting of the Berkeley Linguistics Society: General Session and Parasession on The Place of Morphology in a Grammar (1992), pp. 143-15

Multipath study on the airport surface

International audienceAirport Navigation will require more stringent localization performance requirements than in-flight navigation [1]. GNSS signals (Global Navigation Satellites Systems) can be envisaged to elaborate the aircraft estimate position on the airport surface. To improve the performance of localization on the airport, the errors on GNSS signals particular to the airport environment must be characterized. Most of these errors are well known such as ionosphere error, troposphere error, etc, and do not depend on the airport environment. But to achieve the expected sub-metric performance, it is necessary to better model multipath error for which a model already exists but is valid for operations from en-route down to CAT I only. In this paper, an analysis of real GPS measurements (using code pseudo range measurement, carrier phase measurement, Doppler measurement and the estimate C/N0 ratio measurement) during taxiing operation on the airport surface is conducted. The goal of this paper is to evaluate when multipath occurs and to compare the multipath model (elaborated from the standard deviation of the measurement errors due to multipath) based on those collected measurements in the airport with different models proposed in the literature (not necessary proposed for airport navigation)

Bainville-sur-Madon – Terre Vaine, carrière COGESUD (tranche 2)

Identifiant de l'opération archéologique : 137211 Date de l'opération : 2008 (EX) Cette opération de diagnostic archéologique fait suite à la première tranche de 5 ha sondée en 2005 par M.-P. Koenig. Aucun vestige archéologique n'a été mis au jour sur les 7 ha expertisés lors de cette seconde phase. L'absence de vestiges n'est pas surprenante au vu de l'érosion totale de la formation superficielle. De nouvelles anomalies circulaires et curvilignes, identiques à celles observées en photographi..

Wavelet analyses of electromyographic signals derived from lower extremity muscles while walking or running: A systematic review.

Surface electromyography is often used to assess muscle activity and muscle function. A wavelet approach provides information about the intensity of muscle activity and motor unit recruitment strategies at every time point of the gait cycle. The aim was to review papers that employed wavelet analyses to investigate electromyograms of lower extremity muscles during walking and running. Eleven databases were searched up until June 1st 2017. The composition was based on the PICO model and the PRISMA checklist. First author, year, subject characteristics, intervention, outcome measures & variables, results and wavelet specification were extracted. Eighteen studies included the use of wavelets to investigate electromyograms of lower extremity muscles. Three main topics were discussed: 1.) The capability of the method to correctly assign participants to a specific group (recognition rate) varied between 68.4%-100%. 2.) Patients with ankle osteoarthritis or total knee arthroplasty presented a delayed muscle activation in the early stance phase but a prolonged activation in mid stance. 3.) Atrophic muscles did not contain type II muscle fiber components but more energy in their lower frequencies. The simultaneous information of time, frequency and intensity is of high clinical relevance because it offers valuable information about preand reflex activation behavior on different walking and running speeds as well as spectral changes towards high or low frequencies at every time point of the gait cycle