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Publications

    • Conférence
    • Ingénierie & Outils numériques

    View Selection for Industrial Object Recognition

    The last industrial revolutions and the digital transformation have led to a rise of robotics and to the emergence of the concept of digital twin. A major challenge falls within the update of this virtual representation, so that the supervision operator and the system itself can take appropriate decisions. One way to achieve that is […]

    • Conférence
    • Ingénierie & Outils numériques

    AM modular plant for on-site production

    A dditive manufacturing is a leading technology that is offering flexibility in production : on site production, close to the needs therefore reducing logistics and lead time . Movable solutions exist to deploy an additive manufacturing system on site using container , which is easy to transport N evertheless, there was no movable solution i […]

    • Article
    • Ingénierie & Outils numériques

    Effect of curing temperature on the early and later ages behaviour of Metakaolin blended cement mortars: hydration heat and compressive strength

    Cement is one of the main sources of negative environmental impact of concrete. One way to reduce this impact of concrete could be through the reduction of the cement content. This could be achieved by replacing a part of cement with mineral additives such as fly ash, blastfurnace slag, silica fume, metakaolin (MK), etc. in […]

    • Conférence
    • Apprendre & Innover

    Comportements des PME en termes de pratiques d’innovation ouverte

    Cet article vise à explorer les comportements existants au sein des PME en termes de pratiques d’innovation ouverte. L’objectif est d’aider les praticiens dans leur prise de décision concernant les pratiques à mettre en oeuvre et les stratégies d’innovation à poursuivre selon les caractéristiques organisationnelles des PME. Nos résultats, basés une enquête auprès de 85 […]

    • Conférence
    • Ingénierie & Outils numériques

    SUPERVISED LEARNING BASED APPROACH FOR TURBOFAN ENGINES FAILURE PROGNOSIS WITHIN THE BELIEF FUNCTION FRAMEWORK

    Recent developments in maintenance modeling, powered by data-driven approaches such as Machine Learning (ML), have enabled a wide range of applications. For example, industrial systems coming with a huge operating database make ML an ideal candidate for their predictive maintenance (PdM). PdM is the process of predicting malfunctions using data from equipment monitoring and process […]

    • Autre Production
    • Apprendre & Innover

    Etat de l’art de la pédagogie de l’alternance: enjeux, pratiqeus et principes directeurs

    Il est difficile de penser une ingénierie de l’alternance applicable à tous les contextes. Leur diversité, leurs particularismes, leurs contraintes et leurs ressources sont spécifiques (publics accueillis, rapports aux savoirs, compétences enseignantes, marché de l’emploi, tissus socioéconomiques, équipements et méthodes pédagogiques, etc.). Cela rend d’autant plus ardu l’identification de ses indicateurs d’efficacité. Pour autant, il […]

    • Conférence
    • Ingénierie & Outils numériques

    FPBFT: A Fast PBFT Protocol for Private Blockchains

    Blockchain is an emerging technology that enables storing data and sharing it among many entities without the need for a central organization. Data is stored in an append-only ledger after the majority of participants agree on it. This mechanism is called the consensus, and many protocols are proposed in the literature (PoW, PoS, DPoS, RAFT, […]

    • Conférence
    • Ingénierie & Outils numériques

    FNR-GAN: FACE NORMALIZATION AND RECOGNITION WITH GENERATIVE ADVERSARIAL NETWORKS

    The normalization of in-the-wild faces is a low-cost process which can both improve face recognition performances and reduce the computation complexity of face generation. In this paper, we present an unsupervised Face Normalization and Recognition within Generative Adversarial Networks (FNRGAN). This proposed approach generates and recognizes faces from normalized features of in-the wild faces. We […]

    • Conférence

    Mitosis Detection in Breast Cancer with Deep Learning: A New Approach

    In this work, we propose a new approach for spot- ting mitoses in breast cancer histology images. This new approach involves integrating two publicly accessible datasets following a normalization procedure of color. The mitotic samples are then enhanced by preserving the context to address class imbalance. After this, the candidate mitotic cells are classified into […]

    • Conférence

    Deep learning model based on inceptionResnet-v2 for Finger vein recognition

    In recent years, The pattern of finger veins is widely recognized as an effective biometric for identifying a person. The traditional finger vein identification systems are based on hand- crafted features. However, Finger vein systems has been switched toward automatic features extraction due to the emergence of deep neural networks that are capable of extracting […]

    • Conférence
    • Ingénierie & Outils numériques

    A stochastic approach for extracting community-based backbones

    Large-scale dense networks are very parvasive in various fields such as communication, social analytics, architecture, bio-metrics, etc. Thus, the need to build a compact version of the networks allowing their analysis is a matter of great importance. One of the main solutions to reduce the size of the network while maintaining its characteristics is backbone […]

    • HDR
    • Ingénierie & Outils numériques

    Secure and Reliable Smart Cyber-Physical Systems

    Smart Cyber-Physical Systems (SCPS) are heterogeneous inter-operable autonomous entities that play a crucial role in critical infrastructures. And as a result of supporting novel communication and remote control features, they became more dependent on connectivity, which increased attack surfaces and introduced errors that elevated the likelihood of SCPS errors. Additionally, they may cause new types […]