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Synthetic topology in homotopy type theory for probabilistic programming
No full textInternational audienc
An Optimized Algorithm of General Distributed Diagnosability Analysis for Modular Structures
No full textInternational audienceDiagnosability is an important property that determines at the design stage how accurate any diagnosis algorithm can be on a partially observable system and thus has significant economic impact on the improvement of performance and reliability of complex systems. Very recently distributed approaches for diagnosability began to be investigated since centralized approaches are not realistic for large systems due to the combinatorial explosion of the search space. In this paper, we propose a new optimized algorithm for pattern diagnosability analysis of distributed systems with modular structure, where we obtain the original pattern diagnosability information from the relative components before abstracting the sufficient and necessary information to be propagated to other connected components. Then, the diagnosability decision can be made after global consistency checking at the proper level of the subsystem involved. Our experimental results and complexity analysis illustrate the correctness and efficiency of our approach both in a practical and theoretical way. Finally, we distinguish our work by presenting related works before the conclusion
Purification of pentoses from hemicellulosic hydrolysates without neutralization for sulfuric acid recovery
No full textInternational audienceThe agro-industrial sector generates large amounts of coproducts such as lignocellulosic biomass which could be valorized into many chemicals and bio-based intermediates (sugars, paper pulp, surfactants, polymers or bioethanol). However, in the case of biomass hydrolysis by diluted sulfuric acid, current downstream processes involve a partial or complete neutralization which are not satisfactory for economic and environmental reasons. This work presents a purification process of pentoses from hemicellulosic hydrolysates without neutralization for sulfuric acid recovery. Compared to conventional processes, less energy, water and chemicals are required. Very promising results were obtained at pilot scale with 100 L of wheat bran hydrolysates. The process is based on the combination of ultrafiltration, Conventional electrodialysis and ion-exchange. Ultrafiltration with a 10 kDa organic membrane totally removed harmful macromolecules which precipitate during electrodialysis operation because of pH rise. Till a volumetric concentration factor 3.6, the average flux kept good for industrial application (27 L h(-1)m(-2)). However suspended materials have to be filtered before ultrafiltration. Besides, a 2.5 diafiltration is required to recover most of sugars (99%): Then conventional electrodialysis was performed to recover most of sulfuric acid (80%). The average faradic yield was quite good (80%) and the specific energy consumption of the electrodialysis stack was quite interesting (1.1 kW h per kg of H2SO4 recovered and 8.4 kW h per m(3) of hydrolysate). Finally, the complete demineralization (conductivity < 10 mu S cm(-1)) and discoloration (420 nm absorbance < 0.01) of the sugars solution was performed by ion-exchange and an activated carbon polishing treatment. The sugars purity was close to 100% meanwhile the overall sugars recovery rate reach about 90%. Finally we checked that the reused sulfuric acid solution was as efficient as a fresh one in a second hydrolysis operation of wheat bran. Recovery rates could be increased by a scale-up operation or a continuous mode of the process
A Population-Based Algorithm for Learning a Majority Rule Sorting Model with Coalitional Veto
No full textInternational audienceMR-Sort (Majority Rule Sorting) is a multiple criteria sort-ing method which assigns an alternative a to category Ch when a is better than the lower limit of Ch on a weighted majority of criteria, and this is not true with the upper limit of Ch. We enrich the descriptive ability of MR-Sort by the addition of coalitional vetoes which operate in a symmetric way as compared to the MR-Sort rule w.r.t. to category limits, using specific veto profiles and veto weights. We describe a heuris-tic algorithm to learn such an MR-Sort model enriched with coalitional veto from a set of assignment examples, and show how it performs on real datasets
Bivariate triangular decompositions in the presence of asymptotes
No full textInternational audienceGiven two coprime polynomials and in of degree at most and coefficients of bitsize at most , we address the problem of computing a triangular decomposition of the system .The state-of-the-art worst-case complexities for computing such triangular decompositions when thecurves defined by the input polynomials do not have common vertical asymptotes are for the arithmetic complexity and for thebit complexity, where refers to thecomplexity where polylogarithmic factors are omitted and refers to the bit complexity.We show that the same worst-case complexities can be achieved even when the curves defined by the input polynomials may have common vertical asymptotes.We actually present refined complexities, for the arithmetic complexity and for the bit complexity, where and bound the degrees of and in and , respectively. We also prove that the total bitsize of the decomposition is in
Zr doping on lithium niobate crystals: Raman spectroscopy and chemometrics
No full textInternational audienceRaman measurements were investigated on Zr-doped lithium niobate LiNbO3 crystals with different concentrations. Spectra were treated by fitting procedure and principal component analysis which both provide results consistent with each other. The concentration dependence of the frequency on the main low-frequency optical phonons provides an insight of site incorporation of Zr ions in the host lattice. The threshold concentration of about 2% is evidenced, confirming the interest of Zr doping as an alternative to Mg doping for the reduction of the optical damage in lithium niobate
Stakeholder Power in Industrial Symbioses: A Stakeholder Value Network Approach
No full textInternational audienceForming and sustaining an industrial symbiosis depends on several actors. Actors that have an interest in the symbiosis and the possibility to influence it are called " stakeholders ". According to social exchange theory and resource dependency theory, the power of actors in a network depends on the dependency of other actors on the resources they control. We adapt the stakeholder value network approach from the strategic management literature to the industrial symbiosis context as a means to provide insights into the power of stakeholders of an industrial symbiosis. The approach is applied to a waste incinerator steam network symbiosis case study in France, which has been successfully operated and extended over decades. The results from the case study show that using the stakeholder value network approach enables the assessment of the relative power of symbiosis stakeholders and to identify key resources on which their power is based. We propose the application of the approach to further case studies in order to identify patterns in the power distribution within symbiosis networks
Conception orientée valeurs pour les processus de simulation des architectures systèmes
No full textLa complexité croissante des architectures systèmes engendre des situations dans lesquelles la prise de décision s’avère de plus en plus difficile. Ceci est dû, entre autres, aux modèles de simulation sur lesquels s’appuient les décideurs à un instant donné, mais aussi à l’incertitude liée aux alternatives proposées et aux conséquences possibles de ces décisions [Hassanzadeh, 2013]. Des travaux ont été effectués sur la crédibilité et la communication des résultats de simulation [NASA, 2008, 2016; Blattnig et al., 2008], ainsi que sur l’argumentation dans le cadre de la logique de conception [Regli et al., 2000]. Il y a cependant, en plus de ce que proposent ces méthodes, un besoin de prendre en compte l’incertitude sous un aspect probabiliste afin de considérer la prise de décision avec une approche analytique
Efficient Mining of Subsample-Stable Graph Patterns
No full textInternational audienceA scalable method for mining graph patterns stable under subsampling is proposed. The existing subsample stability and robustness measures are not antimonotonic according to definitions known so far. We study a broader notion of anti-monotonicity for graph patterns, so that measures of subsample stability become antimonotonic. Then we propose gSOFIA for mining the most subsample-stable graph patterns. The experiments on numerous graph datasets show that gSOFIA is very efficient for discovering subsample-stable graph patterns
