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An empirical analysis of the social contract in the Middle East and North Africa region and the role of digitalization in its transformation
No full textInternational audienceThis paper presents an empirical analysis of the social contract (SC) in MENA based on a simple model synthesizing three main characteristics of a SC linking governments and citizens: Participation, Protection, and Provision. Using this 3‐P framework, we focus on the role of provision and protection in determining citizen participation, a question that drew much attention following the recent economic and social developments in MENA. We compare our characterization of the SC in MENA and Organisation for Economic Co‐operation and Development (OECD) countries and find robust empirical evidence that, in MENA, the benefits provided to citizens through improved delivery of basic services have come at the cost of impaired participation. We also find that digital transformation, a potential channel through which the SC may improve, has an inversely U ‐shaped effect suggesting that institutional changes are called for in MENA countries before their SC is comparable to that of OECD countries
Modeling of a biological cell exposed to an electrical pulse: a Discrete Dual Finite Volume method application
No full textInternational audienc
Environmental Constraints for Intelligent Internet of Deep-Sea/Underwater Things Relying on Enterprise Architecture Approach
No full textInternational audienceThrough the use of Underwater Smart Sensor Networks (USSNs), Marine Observatories (MOs) provide continuous ocean monitoring. Deployed sensors may not perform as intended due to the heterogeneity of USSN devices’ hardware and software when combined with the Internet. Hence, USSNs are regarded as complex distributed systems. As such, USSN designers will encounter challenges throughout the design phase related to time, complexity, sharing diverse domain experiences (viewpoints), and ensuring optimal performance for the deployed USSNs. Accordingly, during the USSN development and deployment phases, a few Underwater Environmental Constraints (UECs) should be taken into account. These constraints may include the salinity level and the operational depth of every physical component (sensor, server, etc.) that will be utilized throughout the duration of the USSN information systems’ development and implementation. To this end, in this article we present how we integrated an Artificial Intelligence (AI) Database, an extended ArchiMO meta-model, and a design tool into our previously proposed Enterprise Architecture Framework. This addition proposes adding new Underwater Environmental Constraints (UECs) to the AI Database, which is accessed by USSN designers when they define models, with the goal of simplifying the USSN design activity. This serves as the basis for generating a new version of our ArchiMO design tool that includes the UECs. To illustrate our proposal, we use the newly generated ArchiMO to create a model in the MO domain. Furthermore, we use our self-developed domain-specific model compiler to produce the relevant simulation code. Throughout the design phase, our approach contributes to the handling and controling of the uncertainties and variances of the provided quality of service that may occur during the performance of the USSNs, as well as reducing the design activity’s complexity and time. It provides a way to share the different viewpoints of the designers in the domain of USSNs
A Study of Deep Perceptual Metrics for Image Quality Assessment
No full textSeveral metrics exist to quantify the similarity between images, but they are inefficient when it comes to measure the similarity of highly distorted images. In this work, we propose to empirically investigate perceptual metrics based on deep neural networks for tackling the Image Quality Assessment (IQA) task. We study deep perceptual metrics according to different hyperparameters like the network's architecture or training procedure. Finally, we propose our multi-resolution perceptual metric (MR-Perceptual), that allows us to aggregate perceptual information at different resolutions and outperforms standard perceptual metrics on IQA tasks with varying image deformations
A probabilistic approach for learning and adapting shared control skills with the human in the loop
No full textInternational audienceAssistive robots promise to be of great help to wheelchair users with motor impairments, for example for activities of daily living. Using shared control to provide task- specific assistance – for instance with the Shared Control Templates (SCT) framework – facilitates user control, even with low-dimensional input signals. However, designing SCTs is a laborious task requiring robotic expertise. To facilitate their design, we propose a method to learn one of their core components – active constraints – from demonstrated end- effector trajectories. We use a probabilistic model, Kernelized Movement Primitives, which additionally allows adaptation from user commands to improve the shared control skills, during both design and execution. We demonstrate that the SCTs so acquired can be successfully used to pick up an object, as well as adjusted for new environmental constraints, with our assistive robot EDAN
Verrouillage des lignes de cache pour la lutte contre les attaques par canaux auxiliaires exploitant les mémoires caches
No full textNational audienceLes attaques par canaux auxiliaires exploitant les mémoires caches sont courantes et constituent une menace pour la sécurité des processeurs. Diverses contremesures matérielles et logicielles ont été proposées ces dernières années pour faire face à ces attaques. Cependant, les contremesures logicielles augmentent significativement la taille du code binaire, pénalisant ainsi le temps d'exécution. Les contremesures matérielles nécessitent quant à elles une extension du design existant, entraînant des surcoûts en terme de surface de circuit. Ainsi, dans cette présentation, nous détaillons une contremesure de partitionnement dynamique à grain fin reposant sur une collaboration matériel-logiciel. L'approche proposée étend le jeu d'instructions (ISA, Instruction Set Architecture) RISC-V avec des instructions de verrouillage et de déverrouillage pour permettre à un programme de verrouiller explicitement des lignes de cache dans la mémoire cache de données et de garantir des accès à ces données en temps constant. Notre solution consiste en un partitionnement fin de la mémoire cache, piloté par le logiciel, permettant de verrouiller des données au niveau ligne de cache. Une extension de l'ISA permet d'utiliser le mécanisme en mettant en œuvre deux nouvelles instructions : lock et unlock. Tout accès aux données stockées dans une ligne de cache verrouillée entraîne uncache hit. Une ligne de cache verrouillée ne peut pas être évincée. Le seul moyen de la déverrouiller est que le processus propriétaire exécute l'instruction unlock. Elle peut ensuite être évincée par n'importe quel processus.Nous avons étendu le processeur RISC-V CV32E40P avec un cache de données de premier niveau (L1-D) intégrant notre protection. Les résultats d'implémentation sur cible FPGA montrent un surcoût inférieur à 3% sur une mémoire cache de 8 Ko, 4-way set associative.Une évaluation de sécurité a été réalisée en considérant l'algorithme AES-128 et l'attaque PRIME+PROBE ciblant la SBOX. Les résultats obtenus démontrent que le verrouillage de la SBOX en mémoire cache est efficace contre ce type d'attaque. Il est important de noter que l'impact de la protection sur la taille du binaire est ici inférieur à 1%
Towards high-performance linear potential flow BEM solver with low-rank compressions
No full textInternational audienceThe interaction of water waves with floating bodies can be modelled with linear potential flow theory, numerically solved with the Boundary Element Method (BEM). This method requires the construction of dense matrices and the resolution of the corresponding linear systems. The cost in time and memory of the method grows at least quadratically with the size of the mesh and the resolution of large problems (such as large farms of wave energy converters) can thus be very costly. Approximating some blocks of the matrix by data-sparse matrices can limit this cost. While matrix compression with low-rank blocks has become a standard tool in the larger BEM community, the present paper provides its first application (to our knowledge) to linear potential flows. In this paper, we assess that low-rank blocks can efficiently approximate interaction matrices between distant meshes when using the Green function of linear potential flow. Due to the complexity of this Green function, a theoretical study is difficult and numerical experiments are used to test the approximation method. Typical results on large arrays of floating bodies show that 99% of the accuracy can be reached with 10% of the coefficients of the matrix
Modeling of the Phase Behavior of Carboxylic Acid Systems Using the SAFT-VR Mie DBD Model: Application to the Simulation of the Acrylic Acid Production Process
No full textInternational audienceA new model, referred to as the SAFT-VR Mie DBD model, is proposed to capture the intricate behavior of short carboxylic acids. The new model is based on the SAFT-VR Mie model and integrates a general association term encompassing the formation of doubly bonded dimers (DBD), which enables precise predictions of vaporization enthalpies, densities, heat capacities, and phase behavior for both pure carboxylic acids and their mixtures. This work focuses on the acrylic acid (AA) production process from the oxidation of propene, which involves various unit operations (flash separation, absorption, liquid–liquid extraction, and distillation units). The SAFT-VR Mie DBD model can accurately describe vapor–liquid equilibrium (VLE) data, excess enthalpies, and other essential properties of mixtures containing acetic acid (ACE), acrylic acid (AA), diisopropyl ether (DIPE), water, and various components. To facilitate the practical application of the new thermodynamic model in an industrial context, a dynamic link library (DLL) is developed and made compatible with Simulis Thermodynamics to generate a CAPE-OPEN property package. The process simulations performed on Aspen Plus demonstrate the feasibility of using the SAFT-VR Mie DBD model for designing and optimizing the acrylic acid production process. This study serves as a proof of concept, thereby showcasing the possibility of employing complex thermodynamic models for simulating industrial processes
Coexistence of five domains at single propagating interface in single-crystal Ni Mn Ga shape memory alloy
No full textInternational audienc
InfraParis: A multi-modal and multi-task autonomous driving dataset
No full textInternational audienceCurrent deep neural networks (DNNs) for autonomous driving computer vision are typically trained on specific datasets that only involve a single type of data and urban scenes. Consequently, these models struggle to handle new objects, noise, nighttime conditions, and diverse scenarios, which is essential for safety-critical applications. Despite ongoing efforts to enhance the resilience of computer vision DNNs, progress has been sluggish, partly due to the absence of benchmarks featuring multiple modalities. We introduce a novel and versatile dataset named InfraParis that supports multiple tasks across three modalities: RGB, depth, and infrared. We assess various state-of-the-art baseline techniques, encompassing models for the tasks of semantic segmentation, object detection, and depth estimation. More visualizations and the download link for InfraParis are available at https://ensta-u2is.github.io/infraParis