Un réseau de neurones à décharges pour la reconnaissance de processus spatio-temporels

Traitement des processus dynamiques non stationnaires dans les réseaux de neurones -- Traitement de l'information dans les systèmes nerveux biologiques -- Modèle du réseau de neurones à décharges -- Modèle du neuronne -- Architecture et apprentissage -- Activité d'auto-organisation -- Application à la reconnaisance des chiffres bruités -- Réseau avec mécanisme de > avec récompense -- Traitement des séquences temporelles et détection de mouvement -- Traitement des séquences temporelles -- Détection de mouvement -- Prototype pour un système d'identification du locuteur à l'aide du réseau proposé -- Analyse de la parole par modulation d'amplitude dans le système auditif -- Système d'identification du locuteur -- Traitement des enveloppes par le réseau proposé -- Identification du locuteur basée sur les paramètres de sortie du réseau proposé

A Maximum Entropy Approach to Sentence Boundary Detection of Vietnamese Texts

International audienceWe present for the first time a sentence boundary detection system for identifying sentence boundaries in Vietnamese texts. The system is based on a maximum entropy model. The training procedure requires no hand-crafted rules, lexicon, or domain-specific information. Given a corpus annotated with sentence boundaries, the model learns to classify each occurrence of potential end-of-sentence punctuations as either a valid or invalid sentence boundary. Performance of the system on a Vietnamese corpus achieved a good recall ratio of about 95%. The approach has been implemented to create a software tool named vnSentDetector, a plug-in of the open source software framework vnToolkit which is intended to be a general framework integrating useful tools for processing of Vietnamese texts

Simulation of the Emotion Dynamics in a Group of Agents in an Evacuation Situation

International audienceNowadays, more and more emergency evacuation simulations are used to evaluate the safety level of a building during an emergency evacuation after an accident. The heart of this kind of simulations is the simulation of human behavior because simulation results depend for a big part on how this behavior is simulated. However, human behaviors in a real emergency situation are determined by a lot of cognitive mechanisms. In order to make the simulation more realistic, plenty of factors (e.g. innate characteristics, perception of the environment, internal rules, personality and even emotions) that affect human behaviors must be taken into account. This paper focuses on the influence of emotions, and more precisely on the influence of their dynamics and propagation from an agent to another. The main contribution of this work is the development of a model of emotions taking into account their dynamics and their propagation and its integration in an evacuation simulation. The first results of the simulation show the benefits of considering emotion propagation

Analysis and simulation of a mathematical model of tuberculosis transmission in Democratic Republic of the Congo

According to the World Health Organization reports, tuberculosis (TB) remains one of the top 10 deadly diseases of recent decades in the world. In this paper, we present the modeling, analysis and simulation of a mathematical model of TB transmission in a population incorporating several factors and study their impact on the disease dynamics. The spread of TB is modeled by eight compartments including different groups, which are too often not taken into account in the projections of tuberculosis incidence. The rigorous mathematical analysis of this model is provided, the basic reproduction number (R0) is obtained and used for TB dynamics control. The results obtained show that lost to follow-up and transferred individuals constitute a risk, but less than the cases carrying germs. Rapidly evolving latent/exposed cases are responsible for the incidence increasing in the short and medium term, while slower evolving latent/exposed cases will be responsible for the persistent long-term incidence and maintenance of TB and delay elimination in the population. The numerical simulations of the model show that, with certain parameters, TB will die out or sensibly reduce in the entire Democratic Republic of the Congo (DRC) population. The strategies on which the DRC’s health system is currently based to fight this disease show their weaknesses because the TB situation in the DRC remains endemic. But monitoring contact, detection of latent individuals and their treatment are actions to be taken to reduce the incidence of the disease and thus effectively control it in the population.Mathematical Science

A Hybrid Approach to Word Segmentation of Vietnamese Texts

The original publication is available at www.springerlink.comInternational audienceWe present in this article a hybrid approach to automatically tokenize Vietnamese text. The approach combines both finite-state automata technique, regular expression parsing and the maximal-matching strategy which is augmented by statistical methods to resolve ambiguities of segmentation. The Vietnamese lexicon in use is compactly represented by a minimal finite-state automaton. A text to be tokenized is first parsed into lexical phrases and other patterns using pre-defined regular expressions. The automaton is then deployed to build linear graphs corresponding to the phrases to be segmented. The application of a maximal- matching strategy on a graph results in all candidate segmentations of a phrase. It is the responsibility of an ambiguity resolver, which uses a smoothed bigram language model, to choose the most probable segmentation of the phrase. The hybrid approach is implemented to create vnTokenizer, a highly accurate tokenizer for Vietnamese texts

Effectiveness and safety of in vitro maturation of oocytes versus in vitro fertilisation in women with high antral follicle count : Study protocol for a randomised controlled trial

This work was supported by Ferring grant number 000323 and sponsored by My Duc Hospital.Peer reviewedPublisher PD

TextANIMAR: Text-based 3D Animal Fine-Grained Retrieval

3D object retrieval is an important yet challenging task, which has drawn more and more attention in recent years. While existing approaches have made strides in addressing this issue, they are often limited to restricted settings such as image and sketch queries, which are often unfriendly interactions for common users. In order to overcome these limitations, this paper presents a novel SHREC challenge track focusing on text-based fine-grained retrieval of 3D animal models. Unlike previous SHREC challenge tracks, the proposed task is considerably more challenging, requiring participants to develop innovative approaches to tackle the problem of text-based retrieval. Despite the increased difficulty, we believe that this task has the potential to drive useful applications in practice and facilitate more intuitive interactions with 3D objects. Five groups participated in our competition, submitting a total of 114 runs. While the results obtained in our competition are satisfactory, we note that the challenges presented by this task are far from being fully solved. As such, we provide insights into potential areas for future research and improvements. We believe that we can help push the boundaries of 3D object retrieval and facilitate more user-friendly interactions via vision-language technologies.Comment: arXiv admin note: text overlap with arXiv:2304.0573

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

Modélisation et optimisation de systèmes multiprocesseurs hiérarchiques dans un contexte d'intégration à très grande échelle

Afin de construire des systèmes d'ordinateurs de haute performance utilisant les technologies d'intégration à très grande échelle, une nouvelle architecture de systèmes multiprocesseurs hiérarchiques est proposée. Le présent projet consiste en la modélisation de la performance et l'optimisation de cette architecture. Une méthodologie permettant d'obtenir des modèles d'estimation de performance pour l'architecture hiérarchique est proposée. Le temps moyen requis par un message pour se rendre à sa destination (aussi appelé temps de réponse) est utilisé comme mesure de performance. Ces modèles permettent de prédire la performance d'architectures multi-processeurs hiérarchiques avec une précision adéquate pour une vaste gamme de conditions de trafic et de configuration. Ces modèles permettent également d'optimiser la conception de systèmes hiérarchiques de grande dimension. En effet, puisque le temps de réponse d'un système affecte le temps d'exécution d'une application, la connaissance de la sensibilité de ce dernier en fonction de certains paramètres est essentielle pour la conception de systèmes parallèles de haute performance basés sur cette architecture