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Unravel mechanisms between the carbon and metal species towards biographenic-like materials
No full textInternational audienc
Toward an Innovative Risk- and Opportunity- Oriented System for SMEs’ Decision-Makers
No full textInternational audienceThe COVID-19 crisis has demonstrated numerous weaknesses in Small- and Medium-sized Enterprises (SMEs). Among them, the incapability of top management to make robust strategic decisions in an uncertain environment composed of risks and opportunities, is probably one of the most critical. Unfortunately, such a disrupted context is now the norm. By analyzing the situation, we notice that most of these top management decision-makers use traditional Strategy and Management Accounting methods to make decisions for their business. However, these methods have numerous limits regarding the management of uncertainties. Notably, most of them are deterministic and reactive (i.e., a posteriori analysis) and they often manage risks through pure qualitative approaches. Based on these limitations, this article develops the fundamentals of a first innovative model focused on the management of assets and inspired by Industrial Engineering and Artificial Intelligence risk- and opportunity-oriented tools. The proposed approach intends to support more robust strategic decisions in disrupted contexts. An illustrative case is then developed in order to highlight the potentiality of our approach. Finally, some avenues for future research are exposed regarding the current work which is currently in its infancy.La crise de la COVID-19 a mis en exergue de nombreuses faiblesses dans les entreprises, notamment les petites et moyennes. Parmi ces faiblesses, il en est une symptomatique : l’incapacité des décideurs à prendre des décisions stratégiques robustes dans un contexte incertain et fortement perturbé. Pourtant, un tel contexte, peuplé de risques et d’opportunités, est à considérer comme une nouvelle normalité. Une analyse plus fine de la situation montre que les responsables d’entreprises utilisent principalement des outils issus de la Stratégie et du Contrôle de Gestion pour soutenir leurs décisions. Or, ces outils présentent de nombreuses limites telles que leur ancrage déterministe, leurs analyses ex post, ou encore leur dimension souvent qualitative de la gestion du risque. Le présent travail de recherche propose les bases d’un premier modèle original centré sur la gestion des actifs des entreprises et inspiré du Génie Industriel et de l’Intelligence Artificielle. Ce modèle vise à mieux appréhender les risques et les opportunités dans les mécanismes de prise de décision stratégique. La proposition est illustrée sur un cas d’école permettant de mettre en perspective son potentiel. Des axes de développement futurs sont finalement proposés pour alimenter la suite de ce travail de recherche débuté récemment
Investigating grinding mechanisms and scaling criteria in a ball mill by dimensional analysis
No full textInternational audienceA dimensional analysis of the ball mill process is carried out through the Buckingham-Pi method. The dimensionless quantities identified are discussed and used in order to suggest scaling criteria for ball mills. The flowability and the particle size distribution of an alumina powder ground in laboratory ball mills of various dimensions are compared in order to discuss the influence and the relevance of each dimensionless numbers. Some geometrical, kinetics and dynamic similitudes are highlighted both theoretically and experimentally. In particular, the conservation of the Froude number and the fragmentation number lead to relevant scaling criteria for mills of 1, 2 and 7 L inner volumes. The importance of the ratio between the pebble size and the vessel diameter is also discussed. Finally, the preponderance of the fragmentation number over the number of revolutions of the vessel is interpreted in terms of particle fragmentation mechanisms
Introduction to the minitrack on Disaster Information, Technology, and Resilience in Digital Government
No full textInternational audienceClearly, the year 2020 has shown how sensitive human society is to crisis situations. This is not only a simple matter of fact, this is also and mainly the consequence of the hyper connection of this human society. There is actually no more absorption space for our world and society to absorb any significant disruption and avoid its spreading across the whole planet. However, the progress of human society, in addition to being considered as the main cause of this dangerous evolution, could also provide avenues to deal with it: data science, artificial intelligence, social networks and more globally information technologies are amazing avenues that "in charge" institutions and governments should deeply consider to take the right path to deal with the tremendous next challenges of the century (global warming, pandemics, overpopulation and lack of resources, disbalance north and south, drop of biodiversity, etc.). The DIRECT minitrack of the eGov track of HICSS 54 presents nine great papers addressing these issues but also these perspectives. The following presents each of these articles
Méthode de Monte-Carlo Symbolique pour la caractérisation des propriétés thermiques : application à la méthode flash
No full textNational audienceDuring the characterization, the procedure required to imagine an experiment that can be simulated by a model simple enough to guarantee a quick construction of the solution. The Symbolic Monte-Carlo method appears to be an interesting method for dealing with multi-physical 3D problems, in particular due to its insensitivity to geometrical complexity, the transfer function it allows to produce and its capacity to quickly provide a solution for different values of a given thermophysical parameter. An implementation of the Monte-Carlo Symbolic method is described and studied within the framework of the resolution of a thermal properties identification problem consisting in characterizing the thermal diffusivity by the flash method.Lors de la procédure de caractérisation, l’inverseur est contraint d’imaginer une expérience pouvant être simulée par un modèle suffisamment simple pour garantir une construction rapide de la solution. La méthode de Monte-Carlo Symbolique apparaît comme une méthode intéressante pour traiter les problèmes 3D multi-physiques notamment grâce à son insensibilité a` la complexité géométrique, la fonction de transfert qu’elle permet de produire et sa capacité à fournir rapidement une solution pour différentes valeurs d’un paramètre thermophysique donné. Une mise en œuvre de la méthode de Monte-Carlo Symbolique est décrite et étudiée dans le cadre de la résolution d’un problème d’estimation de propriétés consistant à caractériser la diffusivité thermique par la méthode flash
Routing and scheduling in Home Health Care: A Literature Survey and Bibliometric Analysis
No full textInternational audienceHome Health Care (HHC) agencies aim at providing care and /or services to patients, at their homes, ensuring a quality of service at least equivalent to that given in a hospital, while controlling costs and improving living conditions.The purpose of this paper is to propose a literature survey on ”Home Health Care problems” dealing with routing and scheduling, to provide an overview of the constraints and objectives addressed by Operations Research and Industrial Engineering tools for both theoretical and practical HHC problems.Based on an exhaustive methodology, the current state-of-the-art is reviewed, analyzed, and summarized. We focus not only on the methods used in the different papers studied but also and mainly on constraints and objectives which are specific to the HHC context, particularly highlighting the uncertain and dynamic aspects present in a growing number of papers.This literature survey enables us to identify several research directions, discussed at the end of this paper. It makes it possible for researchers to identify unaddressed problems, or to direct their research towards one or another method according to the constraints and objectives under consideration, while for practitioners, it enables them to see whether their problem has given rise to the development of planning methods.The main contributions of this paper are a synthesis update of the literature dealing with routing and scheduling in the HHC context, a set of comprehensive tables classifying the papers, some discussions on current trends with a focus on the uncertain and dynamic aspects, and future research directions
Learning Local Descriptor for Comparing Renders with Real Images
No full textInternational audienceWe present a method to train a deep-network-based feature descriptor to calculate discriminative local descriptions from renders and corresponding real images with similar geometry. We are interested in using such descriptors for automatic industrial visual inspection whereby the inspection camera has been coarsely localized with respect to a relatively large mechanical assembly and presence of certain components needs to be checked compared to the reference computer-aided design model (CAD). We aim to perform the task by comparing the real inspection image with the render of textureless 3D CAD using the learned descriptors. The descriptor was trained to capture geometric features while staying invariant to image domain. Patch pairs for training the descriptor were extracted in a semisupervised manner from a small data set of 100 pairs of real images and corresponding renders that were manually finely registered starting from a relatively coarse localization of the inspection camera. Due to the small size of the training data set, the descriptor network was initialized with weights from classification training on ImageNet. A two-step training is proposed for addressing the problem of domain adaptation. The first, “bootstrapping”, is a classification training to obtain good initial weights for second training step, triplet-loss training, that provides weights for extracting the discriminative features comparable using l2 distance. The descriptor was tested for comparing renders and real images through two approaches: finding local correspondences between the images through nearest neighbor matching and transforming the images into Bag of Visual Words (BoVW) histograms. We observed that learning a robust cross-domain descriptor is feasible, even with a small data set, and such features might be of interest for CAD-based inspection of mechanical assemblies, and related applications such as tracking or finely registered augmented reality. To the best of our knowledge, this is the first work that reports learning local descriptors for comparing renders with real inspection images
Flexible papers derived from polypyrrole deposited cellulose nanofibers for enhanced electromagnetic interference shielding in gigahertz frequencies
No full textInternational audienceAn array of highly conductive, lightweight and flexible cellulose nanopapers as effective attenuators of electromagnetic radiations within 8.2–12.4 GHz (X band) were formulated via in situ polymerization of pyrrole monomers on to cellulose nanofibers (CNFs). It is quite obvious that the free hydroxyl groups on the surface of CNFs facilitate the formation of intense intermolecular hydrogen bonding with PPy which is envisaged for its excellent electromagnetic shielding performance with an average shielding effectiveness of ca. –22 dB (>99% attenuation) at 8.2 GHz for a paper having 1 mm thickness. The fabricated papers displayed a predominant absorption mechanism (ca. 89%) rather than reflection (ca. 11%) for efficiently attenuating electromagnetic radiations, which has a considerable importance in the modern telecommunication sector. Thus, the designed PPy/CNF papers would replace the conventional metal‐based shields and pave way for the development of green microwave attenuators functioning via a strong absorption mechanism. The PPy/CNF nanopapers exhibited a DC conductivity of 0.21 S/cm, a prime requisite for the development of highly efficient electromagnetic shields. Undoubtedly, such nanopapers can be employed in wide range of applications such as electrodes for supercapacitors and other freestanding flexible paper‐based devices
Blending and foaming thermoplastic starch with poly (lactic acid) by CO 2 ‐aided hot melt extrusion
No full textInternational audienceBiomaterials are materials that can be biodegradable or obtained from renewable resources. Among them, poly (lactic acid) (PLA) and thermoplastic starch (TPS) represent an interesting alternative to replace petro‐sourced thermoplastics. In this study, blends made by TPS addition to PLA were subjected to a foaming process using supercritical CO2‐aided extrusion. Extruder die temperature and CO2 content were the most prominent parameters explaining the structure of the foams obtained. Both parameters were intimately linked since the CO2 flow depends on the melt temperature, the lower the temperature, the higher the CO2 solubility. Therefore, the die temperature was chosen to pilot the process. Whatever the experimental conditions, a 50/50 (in wt%) blend was poorly foamed due to the strong incompatibility between both biopolymers. However, the blend made of 80 wt% PLA and 20 wt% TPS gave evenly foamed samples. In terms of expansion and type of porosity this blend behaved like pure PLA with high porosity, up to 96%, and the presence of a threshold die temperature separating a close cell porosity at lowest temperatures and an open cell structure above the threshold. This temperature threshold was however significantly lower to that obtained with pure PLA
Co-pyrolysis of coal and raw/torrefied biomass: A review on chemistry, kinetics and implementation
No full textInternational audienceThermochemical conversion via co-pyrolysis has the potential to be an efficient route for converting biomass to bio-energy and bio-refinery products. In this review, the implementation of co-pyrolysis of torrefied biomass and coal was critically assessed against co-pyrolysis of raw biomass and coal from both a fundamental and engineering perspective. This evaluation showed fundamental advantages for torrefaction of biomass prior to co-pyrolysis such as a decrease in mass and heat transfer limitations due to an increase in permeability and thermal conductivity of biomass. Co-pyrolysis volatiles may also be upgraded through the catalytic activity of the torrefied biomass surface, producing higher quality oil. Due to properties more similar to coal, torrefied biomass requires less energy for milling (lower operating costs) and can be more easily blended with coal in reactor feeding systems. A state-of-the-art research on co-pyrolysis kinetics revealed that reactivities of blends may be predicted from kinetic parameters of individual feedstocks using an additive approach. To conclude on the preferred reactor design for this process, different reactors were evaluated based on heat transfer mode, operation and product formation. Although both the fluidized bed and rotating cone reactor provide high oil yields, the rotating cone has been more successful commercially. This design shows great promise for specifically co-pyrolysis due to the intimate contact that may be achieved between fuels to maximize synergy. The co-pyrolysis of torrefied biomass and coal may be encouraged from a scientific point of view, however further research is recommended on the effective integration of torrefaction and co-pyrolysis technologies