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9 octobre 2020 | Lesly-Ann Daniel, doctorante au CEA List reçoit le Prix 2020 Jeunes Talents L'Oréal-Unesco pour les Femmes et la Science


A l'occasion de la fête de la science 2020, Lesly-Ann Daniel, 25 ans et originaire d'Orléans, a reçu le prix Jeunes Talents décerné par L'Oréal et l'UNESCO pour ses recherches en informatique.

Lesly-Ann Daniel découvre tardivement l’informatique et s’enthousiasme pour le codage. Concevoir des programmes pour résoudre des problèmes, les faire tourner sur son ordinateur et pouvoir tester immédiatement sa solution l’enchante : la plasticité de l’informatique lui apparaît comme un atout extraordinaire.

Alors qu’elle est étudiante à l’université de Limoges, elle s’intéresse à la sécurité informatique, qui devient par la suite son principal domaine de recherche. Aujourd’hui en deuxième année de thèse, Lesly-Ann Daniel conçoit des logiciels capables d’analyser automatiquement des programmes pour trouver des failles de sécurité ou pour garantir leur absence. Elle analyse en particulier les logiciels cryptographiques afin de s’assurer qu’un potentiel « pirate » ne puisse en extraire des informations confidentielles, ce en mesurant le temps d’exécution de ces programmes.

Pour Lesly-Ann Daniel, le Prix Jeunes Talents s’inscrit dans la continuité d’un parcours marqué par la ténacité, en dehors des filières d’excellence des classes préparatoires et des grandes écoles.

C’est pour elle « une formidable opportunité d’apprendre à croire en soi et en ses capacités, d’autant plus nécessaire lorsqu’on est une jeune femme dans un domaine comme l’informatique où le féminin demeure minoritaire ».

La chercheuse, passionnée de lecture et de cuisine, s’adonne également à l’escalade et à la randonnée. Elle apprécie particulièrement d’assister à des conférences ou de se rendre dans d’autres laboratoires que le sien pour se nourrir d’interactions fertiles entre chercheurs.


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October 5, 2020 | Advanced ictometer for nuclear reactor maintenance

montage visuel 250​In research conducted for a nuclear-industry equipment manufacturer, CEA List, a CEA Tech institute, developed a new ionizing radiation measurement device. Built on the most advanced technology around, the device was designed to meet the requirements of use in nuclear power plants.

Operators who perform maintenance on nuclear reactors use ictometers to measure the neutron flux around the reactor. Strategically placed sensors transform the neutrons detected into electrical pulses, which are in turn centralized and counted by the ictometer. As the older generation of ictometers reaches obsolescence, CEA List, a member of the Carnot Network, drew on its know-how in several fields to design a completely new measurement system for an equipment manufacturer. The powerful, integrated device was developed to meet today's requirements.

CEA List leveraged the know-how available at its PACT sensor and processing lab to develop a multi-channel digital ictometer that can measure radioactivity at several (in this case, four) points simultaneously. CEA List also designed the device's acquisition circuit, which transforms current pulses into voltage pulses, which are then digitized, analyzed, and counted to reliably and reproducibly generate usable data for operators.

The new ictometer also has some additional added-value features like data logs covering several days, charts that make tracking neutron fluxes easier, and a specially designed human-machine interface that displays results in a way that is useful to operators in the field. Other features, such as the integration of step-by-step operator instructions are already on the drawing board.

This end-to-end system does everything from measure to generate actionable data. Not only is it a fine illustration of CEA List's comprehensive digital instrumentation know-how, but it also provides nuclear-industry equipment manufacturers with an innovation that will change the way measurements are taken in the field.

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October 2, 2020 | SACHEMS open-access SHM development and testing platform

sachems 250​CEA List, a CEA Tech institute, is playing an active role in building the SHM (structural health monitoring) industry. The institute now offers development and testing support for SHM technologies at a new platform called SACHEMS.

​​In structural health monitoring (SHM), sensors are integrated into a structure to monitor its condition in real time, providing information that is useful for preventive maintenance, for example. For structures like aircraft, nuclear power plants, wind turbines, and bridges—for which inspection creates undesirable downtime or safety hazards—SHM is an ideal strategy. Although SHM research has been intensive over the last twenty years, solutions have only recently begun to reach the market, thanks mostly to advances in digital technology.

In 2020 CEA List, a member of the Carnot Network, created an open research and innovation platform on the CEA Paris-Saclay campus dedicated exclusively to SHM. The idea is to create a space where academic and industrial stakeholders, technology providers, and the end users of SHM solutions can come together.

SACHEMS, which stands for SAClay High-end Equipment for the Monitoring of Structures, is home to workstations with equipment specific to SHM. SHM solutions providers will be able to use the facility for their proof-of-concept prototyping and testing, benefiting from a shared library of mature enabling technologies and, as a result, shorter development cycles. Partners will have access to servers for their computing and database needs, as well as to the most advanced sensor technologies (piezoelectric, magnetostrictive, fiber optic) and sensor networking tools. The platform is also home to design tools (electronics design for embedded systems) and testing facilities (climatic chambers, electronics test benches).

CEA List hopes to bring not-yet-mature SHM technologies to a stage where they can be scaled up and commercialized on a variety of industrial markets. SACHEMS, made possible in part by financing from the Ile-de-France regional government, will help do exactly that.

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September 24, 2020 | Trusted AI: new advances in the formal validation of neural networks

IAconfiance 250Researchers from CEA List, a CEA Tech institute, have trialed a new approach to the formal validation of neural networks applied to image recognition. Their goal is to improve the safety of features such as pedestrian detection.

When it comes to artificial intelligence, proving that a neural network has been "taught" to do something like recognize pedestrians is a challenge. The formal validation of neural networks applied to image recognition, essential in critical use cases, has been a significant technical hurdle. Before a vehicle's ability to effectively avoid all pedestrians can be tested, for instance, it is important to unambiguously specify what constitutes a pedestrian.

Since it is impossible to describe a pedestrian in mathematical terms, the CEA List Carnot Institute researchers came up with the idea of using image generators (also known as simulators) to "train" neural networks. This avenue seems all the more promising given that simulators are now in widespread use, particularly in the automotive industry, to compensate for the lack of real-world training data. The new specification formalism developed places the simulator at the heart of the validation process, where it serves to formally specify the properties the neural network must satisfy. This allows conventional formal analysis methods, one of CEA List's areas of expertise, to be applied to the network to verify its compliance.

The theoretical results produced were included in the proceedings of the European Conference on Artificial Intelligence (ECAI 2020)[1], while proof-of-concept testing was completed on a scaled-down simulator specially designed for the purpose. The next stage of the process will involve validating the theory on a full-scale system, but this pioneering advance is a significant and tangible step towards trusted AI.

[1] Girard-Satabin, J.; Charpiat, G.; Chihani, Z. & Schoenauer, M. "CAMUS: A Framework to Build Formal Specifications for Deep Perception Systems Using Simulators" ECAI 2020

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September 16, 2020 | A decision-assistance tool for crisis management

expressif 250ExpressIF®, the artificial reasoning platform developed by CEA List, a CEA Tech institute, has been augmented with a spatial data processing module to assist in decision making. The technology is currently being used to manage wildfires, but it also offers potential in other emergency management situations.

Symbolic artificial intelligence algorithms, which simulate complex reasoning and apply it to heterogeneous and uncertain data, can be extremely useful decision-assistance tools in crisis management scenarios. As part of a project backed by the European Regional Development Fund (ERDF) and France's Occitanie regional CLE fund, CEA List, a member of the Carnot Network, partnered with CGX, a company specializing in geographical information systems, to bring the reasoning capabilities of ExpressIF® to wildfire management professionals.

New spatial data processing capabilities were implemented to more effectively assess a potential on-site response and help determine the best course of action. In the first module, the "rules" expressed in structured language (close to natural language) were used not only to model the spatial reasoning to be applied, but also to process both detailed geographic data and weather forecasts to predict the fire's development over time and space. The second module used the temporal reasoning capabilities of ExpressIF® to monitor the temperatures of assets like vehicles and people on the ground, assess the associated risks, and raise alerts in the event of danger.

The human-machine interface (HMI) developed by CEA Tech Occitanie provides a dedicated module for inputting data (locations, events, means, resources, etc.) and displays the results directly on a map in a web app. Further developments to track the rules applied are underway, with the goal of delivering an automated explanation of the results.

The unique spatial and temporal reasoning capabilities of ExpressIF®, combined with its ability to intelligibly process uncertain data, will be extended and applied to other critical scenarios, setting the platform on a course to become a leading AI technology for crisis management.

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