48 research outputs found
Should We Learn Probabilistic Models for Model Checking? A New Approach and An Empirical Study
Many automated system analysis techniques (e.g., model checking, model-based
testing) rely on first obtaining a model of the system under analysis. System
modeling is often done manually, which is often considered as a hindrance to
adopt model-based system analysis and development techniques. To overcome this
problem, researchers have proposed to automatically "learn" models based on
sample system executions and shown that the learned models can be useful
sometimes. There are however many questions to be answered. For instance, how
much shall we generalize from the observed samples and how fast would learning
converge? Or, would the analysis result based on the learned model be more
accurate than the estimation we could have obtained by sampling many system
executions within the same amount of time? In this work, we investigate
existing algorithms for learning probabilistic models for model checking,
propose an evolution-based approach for better controlling the degree of
generalization and conduct an empirical study in order to answer the questions.
One of our findings is that the effectiveness of learning may sometimes be
limited.Comment: 15 pages, plus 2 reference pages, accepted by FASE 2017 in ETAP
Position Models and Language Modeling
International audienceIn statistical language modelling the classic model used is -gram. This model is not able however to capture long term dependencies, \emph{i.e.} dependencies larger than . An alternative to this model is the probabilistic automaton. Unfortunately, it appears that preliminary experiments on the use of this model in language modelling is not yet competitive, partly because it tries to model too long term dependencies. We propose here to improve the use of this model by restricting the dependency to a more reasonable value. Experiments shows an improvement of 45\% reduction in the perplexity obtained on the Wall Street Journal language modeling task
Joule heating and high frequency nonlinear effects in the surface impedance of high Tc superconductors
Using the dielectric resonator method, we have investigated nonlinearities in
the surface impedance Zs = Rs + jXs of YBa2Cu3O7 thin films at 10 GHz as
function of the incident microwave power level and temperature. The use of a
rutile dielectric resonator allows us to measure the precise temperature of the
films. We conclusively show that the usually observed increase of the surface
resistance of YBa2Cu3O7 thin film as function of microwave power is due to
local heating
Using spatially balanced sampling designs to optimise cost-efficiency of long term monitoring programs: application to Manila clam in Arcachon Bay. (3rd best oral communication award)
AFFInternational audienc
Optimizing cost-efficiency of long term monitoring programs by using spatially balanced sampling designs: The case of manila clams in Arcachon bay
ACLInternational audienc
De nouveaux packages pour sélectionner des points d'échantillonnage spatialement équilibrés sous R.
AFFInternational audienc
Listériose et grossesse. Protocole de prise en charge au sein de l’hôpital Necker-Enfants–Malades
International audienceListeriosis is a rare and severe food-borne infection. The clinical and biologica presentation is not specific. Complications such as fetal loss, prematurity < 32 WG (weeks of gestation) and neonatal infection are reported in 80 % of cases. Diagnosis is made by the isolation of Listeria monocytogenes in any sample of maternal, fetal or neonatal origin. Treatment relies on a combination of amoxicillin and gentamicin.La listériose est une infection rare et grave d’origine alimentaire. Sa présentation et biologique est non spécifique et l’infection se complique de perte fœtale, de grande prématurité ou d’infection néonatale dans 80 % des cas. Le diagnostic est porté sur l’identification de Listeria monocytogenes de tout prélèvement d’origine maternelle fœtale ou néonatale. Le traitement repose sur une combinaison d’amoxicilline et de gentamicine
A likelihood-ratio test for identifying probabilistic deterministic real-time automata from positive data (extended abstract)
Software Computer TechnologyElectrical Engineering, Mathematics and Computer Scienc