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Towards flexibility sharing in multi-agent dynamic planning: the case of the health crisis
Get PDFPlanning problems in a crisis context are a highly uncertain environment where health facilities must cooperate in providing health services to their patients. We focus on the health crisis in France due to the COVID19 pandemic. In fact, the lack of appropriate scheduling tools, resources, and communication leads hospitals to be submerged by infected patients and forced to transfer them to other hospitals. In this work we aim to provide a global solution to such planning problems to improve the current French health system. We introduce a cooperative approach called OPPIC (Operational Planning Platform for Inter-healthcare Coordination). OPPIC is based on a decentralized system, where health facilities plan is dynamic, flexible, robust to uncertainty, and respond to goals and optimization criteria. This paper proposed a first planning model to OPPIC and provided a first way of negotiation between health facilities based on their plan's local and global flexibility
Plantes du Paraguay - Etude de quatre plantes bioactives utilisées contre les nématodes gastro-intestinaux
Get PDFL'exploration des propriétés antiparasitaires des plantes indigènes au Paraguay est au centre de ce projet de thèse universitaire basé sur une collaboration entre le Paraguay (Université d'Asunción) et la France (UMR IHAP 1225 INRA / ENVT Toulouse). L'objectif de cette thèse est d'évaluer et de valider l'éventuelle action antiparasitaire des plantes paraguayennes identifiées sur la base d'informations ethno-vétérinaires ou de données photochimiques pour mieux contrôler les nématodes parasites digestifs des petits ruminants (caprins et ovins). Ce projet de thèse s'articulera en 3 étapes. 1) Une étape d'étude prospective et descriptive au Paraguay: a) une enquête ethno-vétérinaire et botanique pour identifier les plantes d'intérêt ayant des propriétés anthelminthiques chez les chèvres et les moutons; b) collecte d'échantillons et production d'extraits. 2) Tests in vitro de stade 2 réalisés en France (UMR IHAP INRA / ENVT Toulouse). Visant à confirmer sur la base d'une série de tests in vitro sur deux espèces NGIS les effets anthelminthiques des extraits de plantes. 3) Analyses Invivo pour valider les effets in vitro. Avec ce projet, nous espérons identifier une activité antiparasitaire des plantes contre les nématodes gastro-intestinaux qui affectent les ruminants et développer leurs applications possibles dans un système agricole traditionnel
Study of the fracture behaviour in hybrid fibers reinforced thermoplastic laminates: Influence of temperature and initial notch orientation
Get PDFThe present work was aimed at investigating the failure of quasi-isotropic fibers reinforced thermoplastic laminates solicited at different testing temperatures. Single-edge-notch bending (SENB) tests were conducted at room temperature (RT) and at a temperature higher than the glass transition temperature (Tg) to investigate the influence of failure mode (depending on initial notch orientation) as well as matrix ductility and toughness (depending on testing temperature) on: (1) damage mechanisms – (2) critical translaminar fracture toughness Gc and (3) G-R curves evolution. The mixed mode fracture toughness GI+II,c is dramatically lower than the mode I fracture toughness GIc, with −52% and −67% decreases, at RT and 150 °C respectively. In 45° notched specimens, most of the fracture energy (about 80%) stems from the mode I failure. Though they are not prominent on fracture, the failure mechanisms associated with mode II are instrumental in limiting the contribution of mode I on fracture behavior. Finally, though a temperature increase has very little influence on GIc, it significantly reduces the value of GI+II,c (−32%). This change primarily results from the formation of plastic-kink bands in compression that are promoted by both the ductility of the polyether ether ketone (PEEK) matrix at T > Tg and the mixed-mode failure
Contribution of an Artificial Intelligence approach to the Guidance/Piloting of PADS
No full textThe dropping of Precision Aerial Delivery Systems (PADS) aims at reaching the “higher, further and more reliable” triptych. Since the 2000s, the development of precise GPS and IMU position systems, and better estimation of wind and flight status have made possible more efficient control of PADS under a ram-air parachute. These allowed drops at ever-higher altitude and at ever further from target point. Nevertheless, the precision of the touchdown, involving the double issue of reaching a target point and the smoothness of the touchdown, has often shown shortcomings or at least a lack of reliability in the expected precision. Among the factors contributing to landing errors, unforeseen wind changes in the surface atmospheric layer are among the main causes of error. This is followed by inaccuracies in status estimation (sensors, real-time management, filtering), then by command modeling errors or also errors related to GNC algorithms. The necessary completeness and the proven complexity of mastering these aspects, generates development costs and significant experimental needs for a result that is not necessarily up to the level of the work.
To overcome these limits of the "physical" (φ) or classic approach, a study was launched within the French Armament Procurement Agency DGA associated with its affiliated school ISAE-SUPAERO, to assess the possible relevance of applying Artificial Intelligence to manage the guidance and control of a load under a ram-air parachute, therefore by a so-called “AI” approach, and hence to improve the precision of PADS. Thus, the work reported here assesses the contribution of Reinforcement Learning (RL) technologies to the guidance of PADS. To do this, we will present the learning platform used, as well as its coupling to a ram-air parachute flight simulator based on
the 9DDL flight dynamics model developed by ONERA [02]. We present the chosen RL algorithm, the learning process and some stability improvements in order to anticipate the reality gap between simulation and reality. A complementary work is also done to evaluate the robustness of the approach as for example here to make the comparison between different models (3DOF to 9DOF). At the end, the obtained results are then compared in the simulator against a classical approach based on the φ laws. These prerequisites lay the foundations for an evaluation of the relevance of the results obtained with regard to a double cross validation using a real mini-PADS prototype (EOLE)
Verification of machine learning based cyber-physical systems: a comparative study
Get PDFIn this paper, we conduct a comparison of the existing formal methods for verifying the safety of cyber-physical systems with machine learning based controllers. We focus on a particular form of machine learning based controller, namely a classifier based on multiple neural networks, the architecture of which is particularly interesting for embedded applications. We compare both exact and approximate verification techniques, based on several real-world benchmarks such as a collision avoidance system for unmanned
aerial vehicles
Structure-preserving discretization of Maxwell’s equations as a port-Hamiltonian system
Get PDFThis work demonstrates the discretization of the boundary-controlled Maxwell equations, recast as a port-Hamiltonian system (pHs). After a reminder on the Stokes-Dirac structure associated with the Maxwell system, we introduce different partitioned weak formulations that preserve the pHs structure, and its associated power balance, at the semi-
discrete level. These weak formulations are compared through numerical applications to closed non-perfectly conducting cavities and open waveguides under transverse approximation
Mangrove microbiota along the urban-to-rural gradient of the Cayenne estuary (French Guiana, South America): drivers and potential bioindicators
Get PDFThe microbial communities inhabiting the Atlantic-East Pacific (AEP) mangroves have been poorly studied, and mostly comprise chronically polluted mangroves. In this study,we characterized changes in the structure and diversity of microbial communities of mangroves along the urban-to-rural gradient of the Cayenne estuary (French Guiana, South America) that experience low human impact. The microbial communities were assigned into 50 phyla. Proteobacteria, Chloroflexi, Acidobacteria, Bacteroidetes, and Planctomycetes were the most abundant taxa. The environmental determinants found to significantly correlated to the microbial communities at these mangroveswere granulometry, dieldrin concentration, pH, and total carbon (TC) content. Furthermore, a precise analysis of the sediment highlights the existence of three types of anthropogenic pressure among the stations: (i) organic matter (OM) enrichment due to the proximity to the city and itswastewater treatment plant, (ii) dieldrin contamination, and (iii) naphthalene contamination. These forms of weak anthropogenic pressure seemed to impact the bacterial population size and microbial assemblages. A decrease in Bathyarchaeota, “Candidatus Nitrosopumilus”, andNitrospira generawas observed inmangroves subjected to OMenrichment. Mangroves polluted with organic contaminants were enriched in Desulfobacteraceae, Desulfarculaceae, and Acanthopleuribacteraceae (with dieldrin or polychlorobiphenyl contamination), and Chitinophagaceae and Geobacteraceae (with naphthalene contamination). These findings provide insights into the main environmental factors shaping microbial communities of mangroves in the AEP that experience lowhuman impact and allowfor the identification of several potential microbial bioindicators of weak anthropogenic pressure
Sizing a Drone Battery by coupling MBSE and MDAO
Get PDFDrones raise highly complex design problems, in particular when energy autonomy of the drone is at stake. In this paper, drone battery design is addressed in terms of coupling two families of design techniques that have been so far too often addressed separately: MBSE (Model-Based Systems Engineering) and MDAO (Multidisciplinary Design Analysis and Optimization)
An RST control design based on interval technique for piezomicropositoning systems with rate-dependent hysteresis nonlinearities
Get PDFWe propose a feedforward-feedback con-trol of piezomicropositioing systems devoted to pre-cise positioning over different operating conditions. Such systems exhibit rate-dependent hysteresis non-linearities and badly damped oscillations character-istics. First, we introduce a rate-dependent Prandtl-Ishlinskii (RDPI) inverse model for feeforward com-pensation of hysteresis. This yields to compensation that can be characterized by an uncertain linear model with disturbances. To model the uncertainties, we suggest to use intervals then we propose a new interval design for a RST structured feedback controller. The proposed design method permits to satisfy prescribed performances. Simulation and experiments on a piezo-electric tube actuator are carried out and demonstrate the efficiency of the proposed control design
Review of AI‐based methods for chatter detection in machining based on bibliometric analysis
Get PDFTo improve the finish and efficiency of machining processes, researchers set out to develop techniques to detect, suppress, or avoid vibration chatter. This work involves tracing chatter detection techniques, from time–frequency signal processing methods (FFT, HHT, STFT, etc.), decomposition (WPD, EMD, VMD, etc.) to the combination with machine learning or deep learning models. A cartographic analysis was carried out to discover the limits of these different techniques and to propose possible solutions in perspective to detect chattering in the machining processes. The fact that human expert detects chatter using simple spectrograms is confronted with the variety of signal processing methods used in the literature and lead to possible optimal detecting techniques. For this purpose, the bibliometric tool R-Tool was used to facilitate a bibliometric analysis using specific means for quantitative bibliometric research and visualization. Data were collected from the Web of Science (WoS 2022) using particular queries on chatter detection. Most documents collected detect chatter with either transformation or decomposition techniques