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The Effect of Haptic Feedback in an Immersive Microsurgery Simulator on VR Training and Skill Transfer
No full textInternational audienceWith the increasing use of immersive simulators in surgical training, there is an emerging emphasis on providing realistic haptic feedback. Although haptic feedback is recognized as necessary for surgical skill acquisition, its role in transferring those skills to real-life situations still needs to be explored. Our study aims to investigate the impact of haptic feedback on basic microsurgery skill acquisition, transfer, and retention, as well as on the user experience during VR training. An immersive simulator was developed to practice a microgrid task under magnification with and without haptic feedback. A similar physical setup with a binocular microscope was also designed to measure skills transfer to the real world. Thirty three volunteers (N = 33) were randomly divided into three participant groups: the haptic feedback group (HG), the no-haptic feedback group (NG), and the control group (CG). All participants performed the task on the physical setup during the pre-post-retention tests. After the pre-test, the first two groups performed six training trials on the immersive simulator, with the HG group receiving haptic feedback while performing the task. The control group did not receive any training. The results show that the HG and NG groups significantly improved their learning curve during training, with no significant differences between them. On the other hand, the haptic feedback led to significantly higher usability and possibility of examination scores than those without haptic feedback. Finally, all the groups improved their time performance on the physical simulator. In addition, the haptic group participants showed a more significant gain in performance in terms of accuracy and error rates. These findings confirm the effectiveness of immersive environments combined with haptic feedback as a valuable training tool, facilitating the transfer of technical skills to real-world applications. Moreover, the results indicate that haptic feedback can also improve the user experience in immersive surgical simulators
L’opérette cinématographique au temps du muet : le cas de Phi-Phi (1918-1927)
No full textInternational audienc
New weighted Riesz-type pointwise inequalities and applications to generalized Sobolev estimates
No full textIn this article we study some new pointwise inequalities between rough singular integral operators and weighted Riesz-type operators. We will thus obtain a wider class of subrepresentation formulas that will lead us to new weighted Sobolev-type inequalities
Does firm size influence the collection of sensitive data? A study of child-orientated apps
No full textInternational audienceHow does firm size affect the privacy protections offered to customers? On the one hand, it could be that larger firms use their size to amass more data. On the other hand, smaller firms may be less careful in their data protection practices, because they have a different perception of risk. Using data from the Google Play Store over a three-year period, we explore this empirical question in the U.S. children's app market. Our findings indicate that larger app developers consistently implement stronger privacy protections, requesting less sensitive data compared to smaller developers. These results hold across empirical approaches, including instrumental variables and the propensity-score matching approach. Additionally, our analysis shows that mergers between developers and sudden increases in size of the user-bases of the product are associated with reduced data collection. We show that newly created and updated apps produced by large developers collect less data compared to existing apps. Our findings indicate a trend toward standardized privacy practices across different national regulatory regimes. This research highlights the potential for growth-driven improvements in data privacy practices among app developers, regardless of their regulatory context
Towards Sustainability in 6G Network Slicing with Energy-Saving and Optimization Methods
No full textThe 6G mobile network is the next evolutionary step after 5G, with a prediction of an explosive surge in mobile traffic. It provides ultra-low latency, higher data rates, high device density, and ubiquitous coverage, positively impacting services in various areas. Energy saving is a major concern for new systems in the telecommunications sector because all players are expected to reduce their carbon footprints to contribute to mitigating climate change. Network slicing is a fundamental enabler for 6G/5G mobile networks and various other new systems, such as the Internet of Things (IoT), Internet of Vehicles (IoV), and Industrial IoT (IIoT). However, energy-saving methods embedded in network slicing architectures are still a research gap. This paper discusses how to embed energy-saving methods in network-slicing architectures that are a fundamental enabler for nearly all new innovative systems being deployed worldwide. This paper's main contribution is a proposal to save energy in network slicing. That is achieved by deploying ML-native agents in NS architectures to dynamically orchestrate and optimize resources based on user demands. The SFI2 network slicing reference architecture is the concrete use case scenario in which contrastive learning improves energy saving for resource allocation
Composite Hydraulic Integration: A New Step Toward Lightweight Hydraulic Robots
No full textInternational audienceNormally, the use of hydraulics in humanoid robots is limited due to their design complexity, heavy weight, and high cost. This paper presents a new methodology for developing hydraulic integrated robotics system with lightweight, high strength, shorter production time and lower cost. This is achieved by combining the additive manufacturing of thermoplastic polymers and the simple forming of strong random fiber composites. A new methodology for fabrication of complex hydraulic integrated parts is explained in detail. The robotic arm of the humanoid hydraulic robot HYDROïD is chosen for implementing the new technique, specifically, the elbow lower part. A theoretical study for different possible 3D printing and reinforcement materials is presented. Then, an optimization method is presented to select the 3D-printed polymer material, the composite, the adequate sizes, and dimensions of the new arm part. Experimental validation and testing of the new part are presented. Moreover, PID gain scheduling controller (PID-GSC) is applied on the robotic arm during validation. The achieved results have shown that the new technique has led to significant weight reduction in the arm components to about 60% of the initial weight with a pressure tolerance of 150 bar. In addition, position tracking has been achieved successfully. Hence, the new attained solution has proved its worthiness with much lower cost and simple fabrication procedures
Self-supervised learning on gene expression data
No full textPredicting phenotypes from gene expression data is a crucial task in biomedical research, enabling insights into disease mechanisms, drug responses, and personalized medicine. Traditional machine learning and deep learning rely on supervised learning, which requires large quantities of labeled data that are costly and time-consuming to obtain in the case of gene expression data. Self-supervised learning has recently emerged as a promising approach to overcome these limitations by extracting information directly from the structure of unlabeled data. In this study, we investigate the application of state-of-the-art self-supervised learning methods to bulk gene expression data for phenotype prediction. We selected three self-supervised methods, based on different approaches, to assess their ability to exploit the inherent structure of the data and to generate qualitative representations which can be used for downstream predictive tasks. By using several publicly available gene expression datasets, we demonstrate how the selected methods can effectively capture complex information and improve phenotype prediction accuracy. The results obtained show that self-supervised learning methods can outperform traditional supervised models besides offering significant advantage by reducing the dependency on annotated data. We provide a comprehensive analysis of the performance of each method by highlighting their strengths and limitations. We also provide recommendations for using these methods depending on the case under study. Finally, we outline future research directions to enhance the application of self-supervised learning in the field of gene expression data analysis. This study is the first work that deals with bulk RNA-Seq data and self-supervised learning
Les acteurs et les mécanismes de l'expertise du XVIe au XIXe siècles
No full textInternational audienceOffrant une perspective originale sur un sujet souvent méconnu, cet ouvrage explore les procédures d'expertise et les acteurs qui les animent entre les XVIe et XIXe siècles. En mettant en dialogue les résultats d'un projet de recherche collectif centré sur la construction parisienne au XVIIIe siècle avec des études de cas provenant de divers domaines et périodes, cet ouvrage enrichit notre compréhension des pratiques d'expertise.Intitulé Pratiques des savoirs entre jugement et innovation. Experts, expertises du bâtiment, Paris 1690-1790, ce projet a permis de constituer deux corpus significatifs : un échantillon de plus de 5 000 procès-verbaux, analysés à travers les prismes du droit, de la technique et de l'économie, ainsi qu'un corpus d'informations sur 242 experts, à finalité prosopographique.Les cas d'étude sont organisés autour de trois axes principaux. Le premier examine le statut de l'expert, révélant une diversité de modèles basés sur la compétence et la renommée, et positionnant ces figures au sein des élites. Le second axe aborde les enjeux de l'expertise, en soulignant non seulement ses implications professionnelles et commerciales, mais aussi ses dimensions politiques souvent inattendues. Enfin, le dernier axe interroge l'autorité de l'expertise, en mettant en lumière ses singularités concurrentielles, les conflits de compétence et les affrontements discursifs qui soulignent sa fonction probatoire.Cet ouvrage constitue une contribution essentielle à l'étude de l'expertise, invitant le lecteur à réfléchir sur les dynamiques de pouvoir et de savoir qui ont façonné les pratiques d'expertise à travers les siècles
Navigating the cloud - A systematic literature review of cloud technologies
No full textInternational audienceCloud storage transforms business landscapes by reshaping how products are innovated, customers are engaged, and securing competitive advantages. This study presents a systematic literature review (SLR) of cloud storage, analyzing its economic impact, adoption trends, pricing models, and strategic implications. Findings indicate that cloud storage adoption varies by industry, with sectors such as finance, healthcare, and education leading due to their high data security and scalability requirements. The study also highlights pricing complexities, where pay-as-you-go, reserved instances, and dynamic pricing models create both cost-saving opportunities and challenges related to vendor lock-in and switching costs. Furthermore, cloud storage plays a crucial role in enhancing business agility, facilitating remote collaboration, and integrating AI, blockchain, and IoT technologies. However, issues related to cybersecurity, regulatory compliance, and pricing transparency remain key concerns. The research underscores the need for robust governance frameworks and multi-cloud strategies to mitigate risks and optimize cloud investments. Future studies should explore long-term cost efficiency, decentralized cloud models, and AI-driven storage optimization to enhance decision-making in cloud adoption
La confiance érodée de la société des flux, un défi éthique majeur
No full textInternational audiencePhilosophe et spécialiste des questions éthiques liées aux technologies numériques, Pierre-Antoine Chardel explore dans cet article les mécanismes qui fragilisent la confiance et interrogent notre capacité à préserver un cadre éthique face aux mutations en cours