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Les Deepfakes changent-ils la donne dans le domaine de la stéganographie d'images numériques en tirant parti de la disparité entre les sources ?
No full textInternational audienceThis work explores the potential of synthetic media generated by AI, often referred to as Deepfakes, as a source of cover-objects for steganography. Deepfakes offer a vast and diverse pool of media, potentially improving steganographic security by leveraging cover-source mismatch, a challenge in steganalysis where training and testing data come from different sources.The present paper proposes an initial study on Deepfakes' effectiveness in the field of steganography. More precisely, we propose an initial investigation to assess the impact of Deepfakes on image steganalysis performance in an operational environment. Using a wide range of image generation models and state-of-the-art methods in steganography and steganalysis, we show that Deepfakes can significantly exploit the cover-source mismatch problem but that mitigation solutions also exist. The empirical findings can inform future research on steganographic techniques that exploit cover-source mismatch for enhanced security
Enhanced Quantitative Wavefront Imaging for Nano-Object Characterization
No full textInternational audienceQuantitative phase imaging enables precise and label-free characterizations of individual nano-objects within a large volume, without a priori knowledge of the sample or imaging system. While emerging common path implementations are simple enough to promise a broad dissemination, their phase sensitivity still falls short of precisely estimating the mass or polarizability of vesicles, viruses, or nanoparticles in single-shot acquisitions. In this paper, we revisit the Zernike filtering concept, originally crafted for intensity-only detectors, with the aim of adapting it to wavefront imaging. We demonstrate, through numerical simulation and experiments based on high-resolution wavefront sensing, that a simple Fourier-plane add-on can significantly enhance phase sensitivity for subdiffraction objects─achieving over an order of magnitude increase (×12)─while allowing the quantitative retrieval of both intensity and phase. This advancement allows for more precise nano-object detection and metrology
Using the MBPCA-OS method on French real estate data to detect the relations between price and Energy and Climate Performance labels
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Creating more with less, frugal innovation as a new design paradigm for sustainability: Creating more with less, frugal innovation as a new design paradigm for sustainability
No full textInternational audienceHumanity is currently facing a series of challenges and crises. In contexts where resources are increasingly scarce and social and environmental problems have intensified, frugal innovation is positioned as a relevant approach to address these issues. Frugal innovation, whose origins lie in India, has sparked interest in the academic community internationally. The growing literature on this approach has shown that entrepreneurs, academics, and activists in developing countries are making interesting contributions to developing ingenious and affordable solutions focused on improving the quality of life and promoting design practices for a transition to sustainability. Scientific research has identified a series of criteria and attributes for frugal innovation. These attributes are focused on functionality, cost reduction, and optimization. However, the literature has also emphasized the need to study and include other cases and geographical contexts, such as Latin America, to consolidate knowledge of this approach. In this article, we make an exploratory analysis of six cases considered as frugal innovations in Mexico. A table of analysis has been constructed from the literature to identify the criteria and relevant strategies to innovate frugally. This study offers a perspective on implementing frugal innovation to enrich traditional approaches to design and innovation, particularly from engineering. The exploratory nature of the cases is limited to the Mexican context and the engineering area. However, the results offer valuable findings for future research from other disciplines, such as management and marketing. The results can support academic, entrepreneurship, and activism projects that aim to innovate frugally.Actualmente, la humanidad se enfrenta a una serie de desafíos y crisis. En contextos donde los recursos naturales son cada vez más escasos y los problemas sociales y ambientales se han intensificado, la innovación frugal se posiciona como un enfoque pertinente para abordar estas problemáticas. La innovación frugal, cuyos orígenes se encuentran en la India, ha despertado el interés en la comunidad académica a nivel internacional. La reciente literatura referente a este enfoque ha demostrado que emprendedores, académicos y activistas en los países en vías de desarrollo están obteniendo contribuciones significativas al desarrollo de soluciones ingeniosas y asequibles, enfocadas en mejorar la calidad de vida y fomentar prácticas de diseño para una transición hacia la sostenibilidad. La investigación ha permitido identificar una serie de criterios y atributos para innovar de manera frugal. Estos atributos están centrados en la funcionalidad, la reducción de costos y la optimización. Sin embargo, la literatura también ha hecho énfasis en la necesidad de estudiar e incluir otros casos y contextos geográficos como el latinoamericano para consolidar el conocimiento sobre este enfoque. En este artículo hacemos un análisis exploratorio de seis casos considerados como innovaciones frugales en el territorio nacional. Se ha construido un cuadro de análisis a partir de la literatura para identificar los criterios y estrategias pertinentes para innovar de manera frugal. Este estudio ofrece una perspectiva de la implementación de la innovación frugal para enriquecer los enfoques tradicionales de diseño e innovación, particularmente desde la ingeniería. La naturaleza exploratoria de casos se limita al contexto mexicano y al área de la ingeniería. Sin embargo, los resultados ofrecen hallazgos valiosos para futuras investigaciones desde otras disciplinas como la administración y el marketing. Los resultados pueden servir de apoyo a proyectos académicos, de emprendimiento y de activismo que apunten a innovar de manera frugal
Matheuristics vs. metaheuristics for joint lot-sizing and dynamic pricing problem with nonlinear demands
No full textInternational audienceThis paper considers a joint dynamic pricing and production planning decisions problem for a profit-maximizing firm that produces and sells multiple products. The objective is to develop a coordinated decision approach for multi-product pricing and lot sizing decisions for a manufacturer considering a limited production capacity. The demand for each product is assumed to be iso-elastic and integrates the complementarity and the substitution effects between the products. First, the problem is formulated as a non-convex mixed integer nonlinear programming model () incorporating capacity constraints, setup costs, and nonlinear demand functions. Then, since the model is nonlinear and non-convex, a set of approximate approaches based on the Genetic algorithm, Late Acceptance Hill Climbing and Simulated Annealing methods are designed to solve this problem. Based on this study, the performances of two variants of approximate methods: matheuristics and metaheuristics are discussed and analyzed. The extensive experimental study, performed on real-world inspired instances, shows that matheuristic methods with setup-variables encoding scheme outperform the rest of the methods. The research outcomes show that coordinating a decision-making process by optimizing both prices and production plans simultaneously can result in significant profit for a company. However, one must consider the joint effect of the parameters of the demand function as well as the impact of the production capacity. This comprehensive understanding enables the company to avoid excessive investments in less lucrative products with lower sales potential, thereby ensuring resource allocation aligns with profitability and market demand
A Multihead Attention Self-Supervised Representation Model for Industrial Sensors Anomaly Detection
No full textInternational audienceIndustrial sensors capture critical information for intelligent manufacturing maintenance. To promote equipment upgrading and manufacturing processes, intelligent decisions, and information learning play an important role. Although deep learning methods historically obtain excellent results, there is always a trade-off between fine-tuning existing networks or designing models from scratch for sensor data processing. In this paper, we propose the multi-head attention self-supervised (MAS) representation model, which is a self-supervised learning-based sensor feature extraction network. To the best of our knowledge, this is the first time a self-supervised contrastive learning method using positive samples that represent multi-dimensional industry sensor data is being used for anomaly detection. We review alternative data augmentation methods proposed for better-representing sensor sequence data. We use this insight to design a new structure that adapts to the temporal characteristics of the application. We apply our method to a real-world water circulation system that uses a variety of industrial sensors. The effectiveness of the proposed MAS methods is demonstrated
Self-Assembly-Driven Biosensors: DNA-Guided Gold Nanoparticles for Information coding
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Near-field characterization of Nb2CTx MXene by non-destructive nearfield microscopy
No full textInternational audienceThe Nb2CTx MXene was synthesized and optically characterized utilizing Photo-induced Force Microscopy (PiFM), a nanoscale imaging technique combining AFM topography mapping and infrared spectroscopy. In both bulk and single/few layered MXene flakes, absorption peaks were observed in the 770 - 1860 cm-1 investigated range. The local IR spectra is compared with broader Fourier-transform infrared (FTIR) and Raman spectroscopy to analyse the material composition. Our findings notably highlight the presence of a characteristic peaks related to surface functional group in both far-field and near-field measurement. The spectra also indicate a strong contribution of niobium oxide in the synthetized material
Exploring collaborative practices in qualitative analysis: The case of GTM
No full textInternational audienceThis doctoral research project aims to study the collaborative practices of social scientists who use Grounded Theory Methodology (GTM). The main objective is to analyze how these researchers organize their collaboration within the analysis process of GTM. The study will first review the literature to understand the evolution of cooperation within GTM, which includes cooperative data collection, joint theorizing, and peer validation. A field study will then focus on social scientists at the University of Liège, including observations, interviews, and scenarios. This fieldwork will be enriched by including design sciences researchers from the Université de Technologie de Troyes. In the final phase of this research, the potential of artificial intelligence and data visualization in survey assistance, case clustering, and theorizing will be explored. To overcome the current limitations of CAQDAS software, a proposal for a collaboration tool aligned with GTM practices will be put forward. This research will contribute to a deeper understanding of researchers’ GTM collaboration practices and tools