Analysis of a finite volume element method for the Stokes problem

In this paper we propose a stabilized conforming finite volume element method for the Stokes equations. On stating the convergence of the method, optimal a priori error estimates in different norms are obtained by establishing the adequate connection between the finite volume and stabilized finite element formulations. A superconvergence result is also derived by using a postprocessing projection method. In particular, the stabilization of the continuous lowest equal order pair finite volume element discretization is achieved by enriching the velocity space with local functions that do not necessarily vanish on the element boundaries. Finally, some numerical experiments that confirm the predicted behavior of the method are provided.

New perspectives in the use of ink evidence in forensic science

Resume : L'utilisation de l'encre comme indice en sciences forensiques est décrite et encadrée par une littérature abondante, comprenant entre autres deux standards de l'American Society for Testing and Materials (ASTM). La grande majorité de cette littérature se préoccupe de l'analyse des caractéristiques physiques ou chimiques des encres. Les standards ASTM proposent quelques principes de base qui concernent la comparaison et l'interprétation de la valeur d'indice des encres en sciences forensiques. L'étude de cette littérature et plus particulièrement des standards ASTM, en ayant a l'esprit les développements intervenus dans le domaine de l'interprétation de l'indice forensique, montre qu'il existe un potentiel certain pour l'amélioration de l'utilisation de l'indice encre et de son impact dans l'enquête criminelle. Cette thèse propose d'interpréter l'indice encre en se basant sur le cadre défini par le théorème de Bayes. Cette proposition a nécessité le développement d'un système d'assurance qualité pour l'analyse et la comparaison d'échantillons d'encre. Ce système d'assurance qualité tire parti d'un cadre théorique nouvellement défini. La méthodologie qui est proposée dans ce travail a été testée de manière compréhensive, en tirant parti d'un set de données spécialement créer pour l'occasion et d'outils importés de la biométrie. Cette recherche répond de manière convaincante à un problème concret généralement rencontré en sciences forensiques. L'information fournie par le criminaliste, lors de l'examen de traces, est souvent bridée, car celui-ci essaie de répondre à la mauvaise question. L'utilisation d'un cadre théorique explicite qui définit et formalise le goal de l'examen criminaliste, permet de déterminer les besoins technologiques et en matière de données. Le développement de cette technologie et la collection des données pertinentes peut être justifiées économiquement et achevée de manière scientifique. Abstract : The contribution of ink evidence to forensic science is described and supported by an abundant literature and by two standards from the American Society for Testing and Materials (ASTM). The vast majority of the available literature is concerned with the physical and chemical analysis of ink evidence. The relevant ASTM standards mention some principles regarding the comparison of pairs of ink samples and the evaluation of their evidential value. The review of this literature and, more specifically, of the ASTM standards in the light of recent developments in the interpretation of forensic evidence has shown some potential improvements, which would maximise the benefits of the use of ink evidence in forensic science. This thesis proposes to interpret ink evidence using the widely accepted and recommended Bayesian theorem. This proposition has required the development of a new quality assurance process for the analysis and comparison of ink samples, as well as of the definition of a theoretical framework for ink evidence. The proposed technology has been extensively tested using a large dataset of ink samples and state of the art tools, commonly used in biometry. Overall, this research successfully answers to a concrete problem generally encountered in forensic science, where scientists tend to self-limit the usefulness of the information that is present in various types of evidence, by trying to answer to the wrong questions. The declaration of an explicit framework, which defines and formalises their goals and expected contributions to the criminal and civil justice system, enables the determination of their needs in terms of technology and data. The development of this technology and the collection of the data is then justified economically, structured scientifically and can be proceeded efficiently.

A Bayesian network approach to the database serch problem in criminal proceedings

Background The 'database search problem', that is, the strengthening of a case - in terms of probative value - against an individual who is found as a result of a database search, has been approached during the last two decades with substantial mathematical analyses, accompanied by lively debate and centrally opposing conclusions. This represents a challenging obstacle in teaching but also hinders a balanced and coherent discussion of the topic within the wider scientific and legal community. This paper revisits and tracks the associated mathematical analyses in terms of Bayesian networks. Their derivation and discussion for capturing probabilistic arguments that explain the database search problem are outlined in detail. The resulting Bayesian networks offer a distinct view on the main debated issues, along with further clarity. Methods As a general framework for representing and analyzing formal arguments in probabilistic reasoning about uncertain target propositions (that is, whether or not a given individual is the source of a crime stain), this paper relies on graphical probability models, in particular, Bayesian networks. This graphical probability modeling approach is used to capture, within a single model, a series of key variables, such as the number of individuals in a database, the size of the population of potential crime stain sources, and the rarity of the corresponding analytical characteristics in a relevant population. Results This paper demonstrates the feasibility of deriving Bayesian network structures for analyzing, representing, and tracking the database search problem. The output of the proposed models can be shown to agree with existing but exclusively formulaic approaches. Conclusions The proposed Bayesian networks allow one to capture and analyze the currently most well-supported but reputedly counter-intuitive and difficult solution to the database search problem in a way that goes beyond the traditional, purely formulaic expressions. The method's graphical environment, along with its computational and probabilistic architectures, represents a rich package that offers analysts and discussants with additional modes of interaction, concise representation, and coherent communication.