Ciclos e arcos rítmicos como estrutura no processo composicional

O presente projeto de graduação em música popular consiste na gravação de uma produção fonográfica com composições próprias e um memorial descritivo que abrange tópicos sobre as construções composicionais, os processos de arranjo das composições, elaborações e discussões sobre o registro gráfico das mesmas e de suas performances, bem como, relatos dos procedimentos de pré-produção, produção e pós-produção do material fonográfico. Reflito sobre ciclos e arcos rítmicos, ideia central nos processos composicionais deste projeto. As composições são inéditas e compreendem em sua maioria, minha produção entre os anos de 2015 a 2018, período em que fiz parte do corpo discente do curso de Bacharelado em Música, Habilitação em Música Popular da UFRGS – Universidade Federal do Rio Grande do Sul

Appendix to the paper entitled: Soft ELECTRE TRI outranking method based on belief functions

International audienceThis short note provides the detailed results of the steps of the ELECTRE TRI (ET) and the Soft ELECTRE TRI (SET) methods presented in [1] that has been applied in the example on a waste disposal selection in an environmental context scenario. ELECTRE TRI (ET) and the Soft ELECTRE TRI (SET) methods have already been published elsewhere: in this note, we only provide a helpful support to engineers or researchers for verifying and testing the implementation of these methods according to their needs

Soft ELECTRE TRI outranking method based on belief functions

International audienceMain decisions problems can be described into choice, ranking or sorting of a set of alternatives. The classical ELECTRE TRI (ET) method is a multicriteria-based outranking sorting method which allows to assign alternatives into a set of predetermined categories. ET method deals with situations where indifference is not transitive and solutions can sometimes appear uncomparable. ET suffers from two main drawbacks: 1) it requires an arbitrary choice of \lambda-cut step to perform the outranking of alternatives versus profiles of categories, and 2) an arbitrary choice of attitude for final assignment of alternatives into the categories. ET finally gives a final binary (hard) assign- ment of alternatives into categories. In this paper we develop a soft version of ET method based on belief functions which circumvents the aforementioned drawbacks of ET and allows to obtain both a soft (probabilistic) assignment of alternatives into categories and an indicator of the consistency of the soft solution. This Soft-ET approach is applied on a concrete example to show how it works and to compare it with the classical ET method

Why Dempster's fusion rule is not a generalization of Bayes fusion rule

International audienceIn this paper, we analyze Bayes fusion rule in details from a fusion standpoint, as well as the emblematic Dempster's rule of combination introduced by Shafer in his Mathematical Theory of evidence based on belief functions. We propose a new interesting formulation of Bayes rule and point out some of its properties. A deep analysis of the compatibility of Dempster's fusion rule with Bayes fusion rule is done. We show that Dempster's rule is compatible with Bayes fusion rule only in the very particular case where the basic belief assignments (bba's) to combine are Bayesian, and when the prior information is modeled either by a uniform probability measure, or by a vacuous bba. We show clearly that Dempster's rule becomes incompatible with Bayes rule in the more general case where the prior is truly informative (not uniform, nor vacuous). Consequently, this paper proves that Dempster's rule is not a generalization of Bayes fusion rule

Analyse multicritères et fusion d'information pour l'expertise et la gestion intégrée des risques naturels en montagne

National audienceLes risques naturels en montagne (crues torrentielles, avalanches) menacent les biens et les personnes avec des conséquences souvent dramatiques. Dans un contexte de connaissances partielles et imparfaites de l'occurrence et de la physique des phénomènes, l'expertise utilise des approches pluridisciplinaires à la fois qualitatives et quantitatives pour identifier les phénomènes, analyser les risques et proposer des stratégies de réduction des risques au travers de mesures structurelles (ouvrages de génie civil) ou non-structurelles (zonage, plans d'alerte). Les analyses dépendent de la qualité et de l' " incertitude " associées à l'information disponible provenant soit de mesures, d'analyses historiques, de témoignages mais aussi d'avis subjectifs, parfois contradictoires exprimés par les experts eux-mêmes. Finalement, les scénarios de phénomènes et les décisions peuvent reposer sur des informations incertaines et contradictoires sans qu'il soit réellement possible d'expliciter la part de vérité, d'imprécision, de conflit ou simplement de méconnaissance dans les hypothèses ayant conduit au résultat. Cet article décrit une méthodologie (dénommée ER-MCDA) d'aide à la décision basée sur l'association de l'analyse multicritères hiérarchique (AHP), les théories des ensembles flous, des possibilités et des fonctions de croyances. Les théories des ensembles flous et des possibilités sont utilisées pour transformer des critères quantitatifs et qualitatifs dans un cadre commun de discernement dans le contexte des théories de Dempster-Shafer (DST) et de Dezert-Smarandache (DSmT). Un problème de décision basée sur l'analyse de la sensibilité d'un site avalanche montre comment la méthode permet de prendre en compte et tracer l'importance des critères, l'imperfection des évaluations et jugements d'expert et la fiabilité des sources. / Rapid mass movements hazards such as mountain rivers (torrents) and snow avalanches put humans and material assets at risk with dramatic consequences. Risk reduction is reached through structural and non-structural measures such as zoning control, preventive information. In a context of lacking knowledge about the natural phenomena, expertise is required to provide analyses for decision and risk management purposes using multi-disciplinary quantitative or qualitative approaches. Expertise depends on the quality and uncertainty of the available information that may result from measures, historical analysis, testimonies but also subjective, possibly conflicting, assessments done by the experts themselves. At the end, phenomena scenarios and decisions may very well rely on very uncertain and conflicting information without being able to really know what was completely true, imprecise, conflicting or simply unknown in the hypotheses leading to the result. A framework mixing fuzzy logics, evidential reasoning and multi-criteria decision analysis (ER-MCDA) is proposed. The Analytic Hierarchy Process (AHP) is used to model the decision and to elicit preferences between criteria. Fuzzy Sets and Possibilities theories are used to transform quantitative and qualitative criteria into a common frame of discernment for Dempster-Shafer Theory (DST) and Dezert-Smarandache Theory (DSmT). A simplified decision sorting problem based on a snow-avalanche risk management problem shows how the use of multi-criteria decision analysis principles and information fusion can be used to characterize and take information quality or imperfection into account for decision purposes. Keywords : Mountain natural hazards, multicriteria decision making, Analytic Hierarchy Process (AHP), information imperfection, information fusion, fuzzy logic, evidence theory, DST, DSmT

Why Dempster’s rule doesn’t behave as Bayes rule with informative priors

International audienceIn this paper, we analyze Bayes fusion rule in details from a fusion standpoint, as well as the emblematic Dempster’s rule of combination introduced by Shafer in his Mathematical Theory of evidence based on belief functions. We propose a new interesting formulation of Bayes rule and point out some of its properties. A deep analysis of the compatibility of Dempster’s fusion rule with Bayes fusion rule is done. Our analysis proves clearly that Dempster’s rule of combination does not behave as Bayes fusion rule in general, because these methods deal very differently with the prior information when it is really informative (not uniform). Only in the very particular case where the basic belief assignments to combine are Bayesian and when the prior information is uniform (or vacuous), Dempster’s rule remains consistent with Bayes fusion rule. In more general cases, Dempster’s rule is incompatible with Bayes rule and it is not a generalization of Bayes fusion rule

Hierarchical proportional redistribution for bba approximation

International audienceDempster’s rule of combination is commonly used in the field of information fusion when dealing with belief functions. However, it generally requires a high computational cost. To reduce it, a basic belief assignment (bba) approximation is needed. In this paper we present a new bba approximation approach called hierarchical proportional redistribution (HPR) allowing to approximate a bba at any given level of non-specificity. Two examples are given to show how our new HPR works

Multi-criteria decision making based on DSmT-AHP

International audienceIn this paper, we present an extension of the multi-criteria decision making based on the Analytic Hierarchy Process (AHP) which incorporates uncertain knowledge matrices for generating basic belief assignments (bba's). The combination of priority vectors corresponding to bba's related to each (sub)-criterion is performed using the Proportional Conflict Redistribution rule no. 5 proposed in Dezert-Smarandache Theory (DSmT) of plausible and paradoxical reasoning. The method presented here, called DSmT-AHP, is illustrated on very simple examples and has been aplied to natural hazards prevention in mountains in a companion paper

Aide à la décision et fusion d'information pour l'expertise des risques naturels : analyse de l'efficacité des ouvrages de protection

National audienceL'expertise permet d'analyser les phénomènes et les risques naturels, proposer des mesures de protection et qualifier leur efficacité. Pour aider à la décision, une approche polyvalente associant l'analyse multi-critères, la logique floue et la théorie des fonctions de croyance est proposée. Elle est compatible et complémentaire avec les principes des méthodes issues de la sûreté de fonctionnement. / Expertise is essential to assess natural hazards and risks, to choose protection measures and evaluate their efficiency. A versatile method, mixing multicriteria decision making and imperfect information related theories (fuzzy logics, evidence theory) is proposed. This approach is compatible and complementary to safety and reliability based methods

Hierarchical DSmP transformation for decision-making under uncertainty

International audienceDempster-Shafer evidence theory is widely used for approximate reasoning under uncertainty; however, the decision-making is more intuitive and easy to justify when made in the probabilistic context. Thus the transformation to approx- imate a belief function into a probability measure is crucial and important for decision-making based on evidence theory framework. In this paper we present a new transformation of any general basic belief assignment (bba) into a Bayesian belief assignment (or subjective probability measure) based on new proportional and hierarchical principle of uncertainty reduction. Some examples are provided to show the rationality and efficiency of our proposed probability transformation approach