GESTION DU RESULTAT ET INTRODUCTION EN BOURSE : CAS DES ENTREPRISES TUNISIENNES

Ce papier étudie la gestion du résultat dans les entreprises tunisiennes non financières lors de leur introduction en bourse durant la période 1998-2003 en utilisant plus qu'un modèle d'estimation des accruals discrétionnaires. Nos résultats ne révèlent en moyenne, aucune gestion du résultat économiquement significative. Une analyse additionnelle, après l'exclusion des entreprises publiques, montre que les entreprises privées gèrent leur résultats à la hausse une année avant l'introduction et, conformément à Teoh et al (1998), ils continuent à le faire après l'introduction pour camoufler l'effet réversible d'une gestion antérieure et atteindre les objectifs optimistes assignés avant l'offre. L'étude met l'accent, aussi, sur l'effet réversible des accruals discrétionnaires et montre que les entreprises ne peuvent pas emprunter indéfiniment des gains futurs pour augmenter leurs gains actuels.Gestion du résultat ; Introduction en bourse ; accruals discrétionnaires

Amélioration des performances des annotateurs sémantiques

RÉSUMÉ Les annotateurs sémantiques jouent un rôle important dans la transition du Web actuel au Web sémantique. Ils s’occupent d’extraire des informations structurées à partir de textes bruts, permettant ainsi de pointer vers des bases des connaissances telles que DBpedia, YAGO ou Babelnet. De nombreuses compétitions sont organisées chaque année pour promouvoir les travaux de recherche de ce domaine. Nous présentons dans ce mémoire notre participation à la compétition Open Knowledge Extraction que nous avons remportée à la conférence European Semantic Web Conference 2016. Dans le cadre de cette compétition, nous avons implémenté une approche générique que nous avons testée sur quatre annotateurs sémantiques. Nous nous concentrons dans ce mémoire à décrire un annotateur sémantique en particulier, DBpedia Spotlight. Nous exposons les différentes limites que présente cet annotateur ainsi que les approches que nous avons développées pour y remédier. Nous avons noté une augmentation d’une moyenne de 20% des performances actuelles de DBpedia Spotlight en testant sur différents corpus. Ces derniers proviennent principalement de journaux internationaux, "Reuters News Stories", "MSNBC" et le "New York Times".----------ABSTRACT Semantic annotators play an important role in the transition from the current Web to the Semantic Web. They take care of extracting structured information from raw texts and thus make it possible to point to knowledge bases such as DBpedia, YAGO or Babelnet. Many competitions are organized every year to promote research works in this field. We present in this thesis our system which was the winner of the Open Knowledge Extraction challenge at the European Semantic Web Conference 2016. For this competition, we implemented a generic approach tested with four semantic annotators. We particularly focus in this thesis on one semantic annotator, DBpedia Spotlight. We present its different limitations along with the approaches that we have developed to remedy them. We noted an improvement of an average of 20% of the current performance of DBpedia Spotlight on different corpora that mainly come from international newspapers, "Reuters News Stories", "MSNBC" and the "New York Times"

Amélioration des performances des annotateurs sémantiques

RÉSUMÉ Les annotateurs sémantiques jouent un rôle important dans la transition du Web actuel au Web sémantique. Ils s’occupent d’extraire des informations structurées à partir de textes bruts, permettant ainsi de pointer vers des bases des connaissances telles que DBpedia, YAGO ou Babelnet. De nombreuses compétitions sont organisées chaque année pour promouvoir les travaux de recherche de ce domaine. Nous présentons dans ce mémoire notre participation à la compétition Open Knowledge Extraction que nous avons remportée à la conférence European Semantic Web Conference 2016. Dans le cadre de cette compétition, nous avons implémenté une approche générique que nous avons testée sur quatre annotateurs sémantiques. Nous nous concentrons dans ce mémoire à décrire un annotateur sémantique en particulier, DBpedia Spotlight. Nous exposons les différentes limites que présente cet annotateur ainsi que les approches que nous avons développées pour y remédier. Nous avons noté une augmentation d’une moyenne de 20% des performances actuelles de DBpedia Spotlight en testant sur différents corpus. Ces derniers proviennent principalement de journaux internationaux, "Reuters News Stories", "MSNBC" et le "New York Times".----------ABSTRACT Semantic annotators play an important role in the transition from the current Web to the Semantic Web. They take care of extracting structured information from raw texts and thus make it possible to point to knowledge bases such as DBpedia, YAGO or Babelnet. Many competitions are organized every year to promote research works in this field. We present in this thesis our system which was the winner of the Open Knowledge Extraction challenge at the European Semantic Web Conference 2016. For this competition, we implemented a generic approach tested with four semantic annotators. We particularly focus in this thesis on one semantic annotator, DBpedia Spotlight. We present its different limitations along with the approaches that we have developed to remedy them. We noted an improvement of an average of 20% of the current performance of DBpedia Spotlight on different corpora that mainly come from international newspapers, "Reuters News Stories", "MSNBC" and the "New York Times"

FICLONE: Improving DBpedia Spotlight Using Named Entity Recognition and Collective Disambiguation

In this paper we present FICLONE, which aims to improve the performance of DBpedia Spotlight, not only for the task of semantic annotation (SA), but also for the sub-task of named entity disambiguation (NED). To achieve this aim, first we enhance the spotting phase by combining a named entity recognition system (Stanford NER ) with the results of DBpedia Spotlight. Second, we improve the disambiguation phase by using coreference resolution and exploiting a lexicon that associates a list of potential entities of Wikipedia to surface forms. Finally, to select the correct entity among the candidates found for one mention, FICLONE relies on collective disambiguation, an approach that has proved successful in many other annotators, and that takes into consideration the other mentions in the text. Our experiments show that FICLONE not only substantially improves the performance of DBpedia Spotlight for the NED sub-task but also generally outperforms other state-of-the-art systems. For the SA sub-task, FICLONE also outperforms DBpedia Spotlight against the dataset provided by the DBpedia Spotlight team

A Novel Synthesis of (Z)-ethyl 3-amino-2-cyano-3-phenyl(or alkyl)acrylate and ethyl- 2-cyano-3-phenyl-3-propionylimino-propanoate

Reaction between ethyl cyanoacetate and imidate, N-acetyl imidate and N-ethoxycarbonyl imidate in basic medium are student. The structure and geometrically configuration of (Z)-ethyl 3-amino-2-cyano-4-phenylbut-2-enoate 3c was established by X-ray diffraction. The functionality in ethyl 2-cyano-3-(ethoxycarbonyl)-3-p-tolylacrylate 7b was exploited to get the desired heterocycle. Â

A Facile Synthesis of Pyrimidoquinazoline Derivatives

A series of pyrimidoquinazoline are prepared via the reaction of ethyl 2,2-dicyano-1-arylvinylcarbamate derivatives 1a-b with methyl 2-aminobenzoate, 1-(2-aminophenyl)ethanone and 2-aminobenzonitrile. The reactivity of compounds 1a-b toward 3-amino-4,6-diphénylnicotinonitrile are studied. The structures of the synthesized compounds are elucidated by X-ray diffraction, IR spectroscopy and nuclear magnetic resonance.Â

Building a binary outranking relation in uncertain, imprecise and multi-experts contexts: The application of evidence theory

AbstractWe consider multicriteria decision problems where the actions are evaluated on a set of ordinal criteria. The evaluation of each alternative with respect to each criterion may be uncertain and/or imprecise and is provided by one or several experts. We model this evaluation as a basic belief assignment (BBA). In order to compare the different pairs of alternatives according to each criterion, the concept of first belief dominance is proposed. Additionally, criteria weights are also expressed by means of a BBA. A model inspired by ELECTRE I is developed and illustrated by a pedagogical example

Analyzing a Bloom Filter Algorithm via a join-the-shortest-queue queuing system

This paper deals with the problem of identifying elephants in the Internet Traffic. The aim is to analyze a new adaptive algorithm based on a Bloom Filter. This algorithm uses a so-called min-rule which can be described as in the supermarket model. This model consists of joining the shortest queue among d queues selected at random in a large number of m queues. In case of equality, one of the shortest queues is chosen at random. An analysis of a simplified model gives an insight into the error generated by the algorithm for the estimation of the number of the elephants. The main conclusion is that, as m gets large, there is a deterministic limit for the empirical distribution of the filter counters. Limit theorems are proved and the limit is identified. It depends on key parameters. The condition for the algorithm to perform well is discussed. Theoretical results are validated by experiments on a trac trace from France Telecom and by simulations

Synthesis and biological evaluation of benzochromenopyrimidinones as cholinesterase inhibitors and potent antioxidant, non-hepatotoxic agents for Alzheimer’s disease

We report herein the straightforward two-step synthesis and biological assessment of novel racemic benzochromenopyrimidinones as non-hepatotoxic, acetylcholinesterase inhibitors with antioxidative properties. Among them, compound 3Bb displayed a mixed-type inhibition of human acetylcholinesterase (IC50 = 1.28 ± 0.03 μM), good antioxidant activity, and also proved to be non-hepatotoxic on human HepG2 cell line.JMC thanks Government of Spain for support (SAF2016-65586-R), JJ and OS thank MH CZ- DRO (UHHK 00179906).We acknowledge support by the CSIC Open Access Publication Initiative through its Unit of Information Resources for Research (URICI)