Auswahl der wissenschaftlichen Literatur zum Thema „Détection d'abus“
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Zeitschriftenartikel zum Thema "Détection d'abus"
Poubelle-Condamin, Christine. „Critères de détection d'abus sexuels à enfants. Présomption - Vraisemblance - Objectivation - Révélation . Étude de trois cas“. Bulletin de psychologie 47, Nr. 415 (1994): 285–98. http://dx.doi.org/10.3406/bupsy.1994.14315.
Der volle Inhalt der QuelleLe Curieux, F., S. Giller, D. Marzini, A. Brice und F. Erb. „Utilisation de trois tests de génotoxicité pour l'étude de l'activité génotoxique de composés organohalogénés, d'acides fulviques chlorés et d'échantillons d'eau (non concentrés) en cours de traitement de potabilisation“. Revue des sciences de l'eau 9, Nr. 1 (12.04.2005): 75–95. http://dx.doi.org/10.7202/705243ar.
Der volle Inhalt der QuelleNICOLAS, B., Ph PAULE, N. Ch ROCHE, L. PAPILLAULT DES CHARBONNERIES und J. C. DEHARO. „Interprétation de l'électrocardiogramme du sujet asymptomatique par le médecin généraliste militaire: une évaluation des pratiques professionnelles“. Revue Médecine et Armées, Volume 42, Numéro 1 (01.02.2014): 59–70. http://dx.doi.org/10.17184/eac.6977.
Der volle Inhalt der QuelleDissertationen zum Thema "Détection d'abus"
Cécillon, Noé. „Combining Graph and Text to Model Conversations : An Application to Online Abuse Detection“. Electronic Thesis or Diss., Avignon, 2024. http://www.theses.fr/2024AVIG0100.
Der volle Inhalt der QuelleOnline abusive behaviors can have devastating consequences on individuals and communities. With the global expansion of internet and the social networks, anyone can be confronted with these behaviors. Over the past few years, laws and regulations have been established to regulate this kind of abuse but the responsibility ultimately lies with the platforms that host online communications. They are asked to monitor their users in order to prevent the proliferation of abusive content. Timely detection and moderation is a key factor to reduce the quantity and impact of abusive behaviors. However, due to the sheer quantity of online messages posted every day, platforms struggle to provide adequate resources. Since this implies high human and financial costs, companies have a keen interest in automating this process. Although it may seem a relatively simple task, it turns out to be quite complex. Indeed, malicious users have developed numerous techniques to bypass the standard automated methods. Allusions or implied meaning are other examples of strategies that automatic methods struggle to detect. While usually performed on individual messages taken out of their context, it has been shown that automatic abuse detection can benefit from considering the context in which the message was posted. In this thesis, we want to focus on the combination of content and structure of conversations to tackle the abuse detection task. Using the textual content of messages is the standard approach which was first developed in the literature. It has the advantage of being easy to set up, but on the other hand, it is vulnerable to text-based attacks such as obfuscation. The structure of the conversation which represent the context is less frequently used as it is more complicated to manipulate. Yet it allows to introduce a contextual aspect which helps detecting abuse occurrences when the text on its own is not sufficient. This context can be modeled as a contextual graph representing the conversation which includes the message. By comparing two methods based on feature engineering on a dataset of conversations extracted from a video games, we could show that a method relying exclusively on conversational graphs and ignoring the content was able to obtain better detection performance. The literature suggest that combining multiple modalities often result in a better detection of abusive messages. We propose multiple strategies to combine the content and structure of conversations and prove that their combination is indeed beneficial to the detection. A limitation of feature-based methods is that they are costly in time and computational resources. Our study also highlights that only a fraction of the computed features are truly relevant for the task. Representation learning methods can be used to mitigate these issues by automatically learning the representations of text and conversational graphs. For graphs, we demonstrated that using edge weights, signs and directions improved the performance. As no method exists for signed whole-graph embedding, we fill this gap in the literature by developing two such methods. We assess them on a newly constituted benchmark of three datasets of signed graphs and show that they perform better than their unsigned counterparts. Lastly, we perform a comparative study of several lexical and graph-embedding method for abuse detection by applying them to our dataset of conversations. Our results show that they perform better than feature-based approaches on text and are slightly less effective on graphs. Still, they obtain promising results given that they are completely task independent, much more scalable and time-efficient than feature-based approaches
Hudelot, Patrick. „Détection et analyse par effet de lentille gravitationnelle d'amas de galaxies“. Toulouse 3, 2005. http://www.theses.fr/2005TOU30285.
Der volle Inhalt der QuelleThe cartography of the mass in galaxy clusters compared to the output of numerical simulations is a powerful test to constrain cosmological parameters. The originality of the gravitationnal lensing analysis presented in the first part is the large use of new statistical bayesian techniques to measure the shape of galaxies and reconstruct the final mass maps. This formalism allowed a precise determination of the NFW profile of the cluster Cl0024. The second part presents the project of a joined galaxy cluster detection both with the Sunyaev-Zel'dovich effect (radio) et the Red Cluster Sequence (optical). This method is based of this identification of colour sequences of early type galaxies in cluters. The implementation has been tested on a subsample of images of the complete survey. Finally a chapter is devoted to the tools used to reduce the wide field images used in this work
Kernalléguen, Angéline. „Caractérisation et localisation des xénobiotiques dans les cheveux par spectrométrie de masse Maldi“. Thesis, Aix-Marseille, 2018. http://www.theses.fr/2018AIXM0754.
Der volle Inhalt der QuelleHair analysis is now recognized as a relevant tool in the field of toxicology. It provides a precise history of an individual’s exposure to drugs, whether it is a punctual or repeated consumption.Matrix-Assisted Laser Desorption/Ionization (MALDI) has many advantages over conventional techniques: the amount of hair needed is reduced, the sample preparation is simplified and the images are acquired with high spatial resolution (~ 100 μm).MALDI (MALDI-MSn) imaging allowed us to characterize and map the evolution of drugs amounts along the hair with very spatial resolution avoiding long and complex pre-sample preparation.MALDI coupled to Microaarays for Mass Spectrometry (MAMS) allowed us to develop a method for semi-quantitation of cocaine, benzoylecgonine, ecgonine methyl ester and cocaethylene using 1 mg of hair and 2 hours of extraction; the results are well correlated with a validated quantification method. This method is relevant when urgent results are required.In total, the development of these two applications demonstrates the relevance of MALDI mass spectrometry in the toxicological analysis of hair. The prospects are to improve these protocols in order to transpose them routinely and to develop large screening methods by MALDI mass spectrometry
Schwab, Siméon. „Suivi visuel multi-cibles par partitionnement de détections : application à la construction d'albums de visages“. Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2013. http://tel.archives-ouvertes.fr/tel-00919425.
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