Modélisation des attaquants et de la réputation dans les réseaux ad hoc mobiles

Attaques et mécanismes de prévention dans les RAHM -- Modèle de relation entre les RAHM et les attaquants -- Validation du modèle et résultats

Anomaly Detection in Automated Fibre Placement: Learning with Data Limitations

Conventional defect detection systems in Automated Fibre Placement (AFP) typically rely on end-to-end supervised learning, necessitating a substantial number of labelled defective samples for effective training. However, the scarcity of such labelled data poses a challenge. To overcome this limitation, we present a comprehensive framework for defect detection and localization in Automated Fibre Placement. Our approach combines unsupervised deep learning and classical computer vision algorithms, eliminating the need for labelled data or manufacturing defect samples. It efficiently detects various surface issues while requiring fewer images of composite parts for training. Our framework employs an innovative sample extraction method leveraging AFP's inherent symmetry to expand the dataset. By inputting a depth map of the fibre layup surface, we extract local samples aligned with each composite strip (tow). These samples are processed through an autoencoder, trained on normal samples for precise reconstructions, highlighting anomalies through reconstruction errors. Aggregated values form an anomaly map for insightful visualization. The framework employs blob detection on this map to locate manufacturing defects. The experimental findings reveal that despite training the autoencoder with a limited number of images, our proposed method exhibits satisfactory detection accuracy and accurately identifies defect locations. Our framework demonstrates comparable performance to existing methods, while also offering the advantage of detecting all types of anomalies without relying on an extensive labelled dataset of defects

Anomaly detection in automated fibre placement: learning with data limitations

Introduction: Conventional defect detection systems in Automated Fibre Placement (AFP) typically rely on end-to-end supervised learning, necessitating a substantial number of labelled defective samples for effective training. However, the scarcity of such labelled data poses a challenge.Methods: To overcome this limitation, we present a comprehensive framework for defect detection and localization in Automated Fibre Placement. Our approach combines unsupervised deep learning and classical computer vision algorithms, eliminating the need for labelled data or manufacturing defect samples. It efficiently detects various surface issues while requiring fewer images of composite parts for training. Our framework employs an innovative sample extraction method leveraging AFP’s inherent symmetry to expand the dataset. By inputting a depth map of the fibre layup surface, we extract local samples aligned with each composite strip (tow).Results: These samples are processed through an autoencoder, trained on normal samples for precise reconstructions, highlighting anomalies through reconstruction errors. Aggregated values form an anomaly map for insightful visualization. The framework employs blob detection on this map to locate manufacturing defects.Discussion: The experimental findings reveal that despite training the autoencoder with a limited number of images, our proposed method exhibits satisfactory detection accuracy and accurately identifies defect locations. Our framework demonstrates comparable performance to existing methods, while also offering the advantage of detecting all types of anomalies without relying on an extensive labelled dataset of defects

Synthetic anionic surfaces can replace microparticles in stimulating burst coagulation of blood plasma

Biomaterials are frequently evaluated for pro-coagulant activity but usually in the presence of microparticles (MPs), cell-derived vesicles in blood plasma whose phospholipid surfaces allow coagulation factors to set up as functional assemblies. We tested the hypothesis that synthetic anionic surfaces can catalyze burst thrombin activation in human blood plasma in the absence of MPs. In a thromboelastography (TEG) assay with plastic sample cups and pins, recalcified human citrated platelet-poor plasma spontaneously burst-coagulated but with an unpredictable clotting time whereas plasma depleted of MPs by ultracentrifugation failed to coagulate. Coagulation of MP-depleted plasma was restored in a dose-dependent manner by glass microbeads, hydroxyapatite nanoparticles (HA NPs), and carboxylic acid-containing anionic nanocoatings of TEG cups and pins (coated by glow-discharge plasma-polymerized ethylene containing oxygen, L-PPE:O with 4.4 and 6.8 atomic % [COOH]). Glass beads lost their pro-coagulant activity in MP-depleted plasma after their surfaces were nanocoated with hydrophobic plasma-polymerized hexamethyl disiloxane (PP-HMDSO). In FXII-depleted MP-depleted plasma, glass microbeads failed to induce coagulation, however, FXIa was sufficient to induce coagulation in a dose-dependent manner, with no effect of glass beads. These data suggest that anionic surfaces of crystalline, organic, and amorphous solid synthetic materials catalyze explosive thrombin generation in MP-depleted plasma by activating the FXII-dependent intrinsic contact pathway. The data also show that microparticles are pro-coagulant surfaces whose activity has been largely overlooked in many coagulation studies to-date. These results suggest a possible mechanism by which anionic biomaterial surfaces induce bone healing by contact osteogenesis, through fibrin clot formation in the absence of platelet activation.Fil: Contreras García, Angel. École Polytechnique de Montréal. Department of Engineering Physics. Groupe de Physique et Technologie des Couches Minces; CanadáFil: D'elía, Noelia Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentina. École Polytechnique de Montréal. Department of Engineering Physics; CanadáFil: Desgagné, Maxime. École Polytechnique de Montréal. Department of Engineering Physics; CanadáFil: Lafantaisie Favreau, Charles Hubert. École Polytechnique de Montréal. Department of Engineering Physics; CanadáFil: Rivard, Georges Étienne. CHU Sainte-Justine; CanadáFil: Ruiz, Juan Carlos. Universidad Autónoma Metropolitana; MéxicoFil: Wertheimer, Michael Robert. École Polytechnique de Montréal. Department of Engineering Physics. Groupe de Physique et Technologie des Couches Minces; Canadá. École Polytechnique de Montréal. Institute of Biomedical Engineering; CanadáFil: Messina, Paula Verónica. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; ArgentinaFil: Hoemann, Caroline Dieckmann. École Polytechnique de Montréal. Department of Engineering Physics; Canadá. École Polytechnique de Montréal. Institute of Biomedical Engineering; Canad

Advanced laboratory testing methods using real-time simulation and hardware-in-the-loop techniques : a survey of smart grid international research facility network activities

The integration of smart grid technologies in interconnected power system networks presents multiple challenges for the power industry and the scientific community. To address these challenges, researchers are creating new methods for the validation of: control, interoperability, reliability of Internet of Things systems, distributed energy resources, modern power equipment for applications covering power system stability, operation, control, and cybersecurity. Novel methods for laboratory testing of electrical power systems incorporate novel simulation techniques spanning real-time simulation, Power Hardware-in-the-Loop, Controller Hardware-in-the-Loop, Power System-in-the-Loop, and co-simulation technologies. These methods directly support the acceleration of electrical systems and power electronics component research by validating technological solutions in high-fidelity environments. In this paper, members of the Survey of Smart Grid International Research Facility Network task on Advanced Laboratory Testing Methods present a review of methods, test procedures, studies, and experiences employing advanced laboratory techniques for validation of range of research and development prototypes and novel power system solutions

Fast interferometric second harmonic generation microscopy

We report the implementation of fast Interferometric Second Harmonic Generation (I-SHG) microscopy to study the polarity of non-centrosymmetric structures in biological tissues. Using a sample quartz plate, we calibrate the spatially varying phase shift introduced by the laser scanning system. Compensating this phase shift allows us to retrieve the correct phase distribution in periodically poled lithium niobate, used as a model sample. Finally, we used fast interferometric second harmonic generation microscopy to acquire phase images in tendon. Our results show that the method exposed here, using a laser scanning system, allows to recover the polarity of collagen fibrils, similarly to standard I-SHG (using a sample scanning system), but with an imaging time about 40 times shorter. OCIS codes: (180.4315) Nonlinear microscopy, (190.2620) Harmonic generation and mixing, (170.6935) Tissue characterization, (190.4180) Multiphoton processes, (190.4710) Optical nonlinearities in organic material

Calibration procedure for enhanced mirror artifact removal in full-range optical coherence tomography using passive quadrature demultiplexing

SignificancePassive quadrature demultiplexing allows full-range optical coherence tomography (FR-OCT). However, imperfections in the wavelength- and frequency-response of the demodulation circuits can cause residual mirror artifacts, which hinder high-quality imaging on both sides of zero delay.AimWe aim at achieving high mirror artifact extinction by calibrated postprocessing of the FR-OCT signal.ApproachWe propose a mathematical framework for the origin of the residual mirror peaks as well as a protocol allowing the precise measurement and correction of the associated errors directly from mirror measurements.ResultsWe demonstrate high extinction of the mirror artifact over the entire imaging range, as well as an assessment of the method's robustness to time and experimental conditions. We also provide a detailed description of the practical implementation of the method to ensure optimal reproducibility.ConclusionThe proposed method is simple to implement and produces high mirror artifact extinction. This may encourage the adoption of FR-OCT in clinical and industrial systems or loosen the performance requirements on the optical demodulation circuit, as the imperfections can be handled in postprocessing