Abstract: The invention includes a method for calibrating an object re-identification solution implementing an array of several cameras. For at least one pair of two cameras from among the several camera, the method includes detecting objects in images taken by each of the two cameras, and computing a normalized distance between a digital signature of each object detected by one of the two cameras, and that of each different object detected by the other one of the two cameras. The method also includes determining, as a function of said normalized distances, a distance threshold, called re-identification threshold, that will be used for re-identifying objects in the images taken by the two cameras. The invention also includes a computer program and a device implementing such a calibration method, and a method and a system for re-identifying individuals calibrated by such a calibration method.

Abstract: Disclosed is a method for test traffic generation, at test-sending switches for a network of calculation nodes, and of inspection of this test traffic, at test-receiving switches of this network, including: the generation and sending of test traffic, at least at a selected test-sending input or output port of one selected test-sending switch, sent to at least one selected test-receiving input or output port of a selected test-receiving switch, where the test traffic is generated and sent by a traffic generation component configured as an additional input of the selected test-sending input or output port, where the test traffic is inspected by a traffic inspection component configured for filtering the output of the selected test-receiving input or output port.

Abstract: A device (DS) monitors a process using at least one electronic device (EE1-EE4) in operation and generating first data of a metric. This device (DS) comprises: learning means (MA) configured to analyse automatically second data which are representative of events that have occurred in the course of the process, in order to determine anomalies of a chosen type, and then automatically determine an indicator representative of this metric, then a correlation between these determined anomalies and this indicator, and then at least one rule defining this correlation, and monitoring means (MS1) configured to analyse newly generated first data periodically, and group by group, by checking whether at least one value of the indicator determined on the basis of the aforesaid data satisfies this determined rule, in order to predict the occurrence of the anomaly in a future group of first data when this at least one value satisfies this rule.

Abstract: A computing system for adjusting voltage regulation including a main processing module, a secondary processing module that executes requested computation tasks, and a voltage regulation module connected to the secondary processing module that regulates its output voltage according to a regulation law depending on at least one regulation parameter. The system also includes a first digital bus (that transfers requested computation tasks from the main processing module to the secondary processing module and transfers results of the requested computation tasks from the secondary processing module to the main processing module. The system also includes a second digital bus that transfers regulation parameters from the main processing module to the voltage regulation module.

Abstract: Apparatus (1) for automatically conducting an interview over a telecommunication network (4), with at least one candidate party (2a, 2b, . . . 2N) to an open job position; comprising means for: selecting (S0) a candidate party; initiating (S1) a communication session between the candidate party and an automated interviewing party; monitoring (S2) the communication session by receiving an audio stream; converting (S3) language of said audio stream into text data determining (S4), from said text data, at least first understandability quality features (UQFA, UQFG) and an information quality feature (IQF), said first understandability quality feature being representative of at least word articulation and grammar correctness within said language, and said information quality feature being representative of a comparison of the semantic content of the audio stream with an expected content; assessing (S5) a matching value of the candidate party.

Abstract: An electronic device for identifying and tracking at least one target, including: a receiver module configured to receive images from a network of image sensors; a determination module configured to determine visual signatures of a respective target from the received images, each visual signature being determined from a respective image including a representation of the target, each visual signature being in the form of a vector in multi-dimensional space; a first filtering module configured to filter the visual signatures; a computation module configured to compute a reference visual signature, in multi-dimensional space; a detection module configured to detect an appearance of the target, and a second filtering module.

Abstract: A method for scheduling computing tasks on a supercomputer including offline reinforcement learning (OFRL) of a scheduler on a database (LDB). The database includes at least one execution history (HIST) that includes the state (LHPCS) of a learning supercomputer at several moments (T, T-1); the actions (LACT) related to the scheduling of learning tasks on the learning supercomputer at those moments (T); and a reward (REW) related to each task. The method also includes the use of the scheduler trained on the computing tasks to be scheduled.

Abstract: The present disclosure relates to a computing system for executing hybrid programs, said computing system comprising: hardware resources comprising quantum computing resources and classical computing resources, said quantum computing resources comprising one or more quantum computers; software resources to be executed on the hardware resources; wherein the software resources comprise a plurality of processing modules comprising interfaces of two possible types referred to as upstream interface and downstream interface, wherein said plurality of processing modules comprises: at least one quantum processing module for each quantum computer, wherein each quantum processing module comprises an upstream interface; a plurality of plugin modules, wherein each plugin module comprises both an upstream interface and a downstream interface; wherein a hybrid program is built by connecting at least one plugin module and one quantum processing module.

Abstract: The present disclosure relates to a computing system comprising a classical computer, an analog quantum computer and a digital quantum computer, said computing system comprising: a digital quantum processing, DQP, module comprising an input interface for receiving a quantum circuit to be executed by the digital quantum computer; an analog quantum processing, AQP, module comprising an input interface for receiving a temporal schedule to be executed by the analog quantum computer; a digital to analog converting, DAC, module comprising an input interface for receiving a quantum circuit and an output interface for outputting a temporal schedule; wherein a same format is used on the input interfaces of both the DQP module and the DAC module, and a same format is used on both the output interface of the DAC module and the input interface of the AQP module.

Abstract: This invention relates to a method of building a hybrid quantum-classical computing network, comprising: a first step of transformation of an application composed of services into a Petri net including both Petri places (8, 9) and Petri transitions (81, 82, 91-94) between said Petri places (8, 9), any said Petri place (8, 9) corresponding to: either a first type building block corresponding to any quantum processing unit (8) which processes a job into a result, or a second type building block corresponding to any plugin unit (9), which converts a job into another job and/or a result into another result, any Petri transition (81, 82, 91-94) corresponding to any link between two building blocks (8, 9), all said links (81, 82, 91-94) being formatted so as to make any building block (8, 9) interchangeable, a second step of transformation of said Petri net into a hybrid quantum-classical computing network, replacing any building block by its corresponding unit (8, 9), interconnecting all said corresponding units (

Abstract: A High Performance Computing (HPC) machine comprising several computing processors interconnected through at least one network, and at least one primary management unit, in a vicinity of at least one computing processor. The at least one primary management unit powers on the at least one processor. The at least one primary management unit (comprises a random data item generator, and a secure storage memory for storing a secret data item, common to all computing processors of the HPC machine, and used for authentication of each computing processor of the HPC machine for data exchange in the HPC machine.

Abstract: A method for automatically sending containment instructions from a central containment component contained in a public cloud to an endpoint contained inside a company network where a malicious activity has been detected. The method includes a central containment component elaborating and placing a secured containment instruction inside a messaging queue of the central containment component, and a component, called edge containment component, running inside the company network, periodically polling the messaging queue service by creating an outgoing connection from the company network to the central containment component in the public cloud. When the edge containment component detects the containment instruction, the edge containment component retrieves, decodes and sends the containment instruction to the endpoint inside the company network.

Abstract: A computer-implemented method for training a neural network providing a digital signature for each image given as input to the neural network. The method includes a first training phase of the neural network with a set of training images and a training algorithm aiming to minimize a first cost function. The method also includes a second training phase including at least one iteration of providing an image originating from said set of training images to said neural network in order to obtain a so-called real signature, generating at least one so-called artificial signature from said real signature, calculating an error based upon said real and artificial signatures, and updating at least one layer of said neural network, based upon said error, in order to minimize a second cost function. A neural network trained by the method and to a method for object re-identification on images implementing the neural network.

Abstract: Disclosed is a system and a method for connecting at least one electronic card to an electronic board of a computer device, the system including an electronic board, equipped with a plurality of connectors for connecting at least one electronic cards to the electronic board, and slots for connecting at least one component to the electronic board. The at least one electronic card are substantially perpendicular to the electronic board. The system further includes a first supporting means being configured such that the at least one electronic card is first mounted onto the first support before the first support is placed above the electronic board in the vertical direction. The system further includes a second support installed underneath the electronic board in the vertical direction. The system includes further ejection mechanism and insertion mechanism. The system for connecting may include a plurality of electronic boards.

Abstract: A method of representing a distributed computing system, the distributed computing system comprising a plurality of processing devices connected together according to a predefined topology. The method comprising receiving at least one piece of data from an activity log file relating to at least one processing device among the plurality of processing devices, receiving at least one metric relating to at least one processing device among the plurality of processing devices, receiving at least the predefined topology of the distributed computing system, constructing a graph representative of a distributed computing system operation, the graph comprising the data item extracted from the received log file, the received metric, and the received topology, and embedding at least one part of the graph to obtain at least one state vector representing the at least one part of the embedded graph.

Abstract: A communication method for the secure management of keys and identities of an Object manufactured by a Manufacturer having a Manufacturer key pair (Ksman, Kpman) and a client having a Client key pair (Ksclient, Kpclient), that is carried out at least partially on a decentralized blockchain database by generating by the Manufacturer two diversified symmetric keys from its key pair and from diversifiers, sharing keys with the object, publishing and recording the decentralized identifier (DID) in the database, wherein when a Client purchases the object from the Manufacturer, providing the identifier of the object DID by the Manufacturer, updating the blockchain, when the object is initially switched on, auto-enrolling by generating new symmetric keys, sending two new encrypted diversifiers to the client with the public client key, publishing and recording new encrypted diversifiers with the public client key in the blockchain.

Abstract: The invention concerns a storage method for storing, on data servers (3, 4), data file (5, 61 to 64) slices (51 to 58) from the execution of a plurality of processes (65 to 68) of one or more applications (83, 85), comprising: distributing the stored data file (5, 61 to 64) slices (51 to 58) over different data servers (3, 4), characterized in that: this distribution is carried out in such a way that the data file (5, 61 to 64) slices (51 to 58) likely to be subsequently accessed simultaneously by different application (83, 85) processes (65 to 68) are stored on different data servers (3, 4) so as to reduce the subsequent access, to each of all or part of these data servers (3, 4) by too many application (83, 85) processes (65 to 68) simultaneously, and in that: the determination of the data file (5, 61 to 64) slices (51 to 58) likely to be subsequently accessed simultaneously by different application (83, 85) processes (65 to 68) has been carried out, during a prior phase of executing these application (83,

Abstract: The invention relates to a method (for determining calibration data for an airborne goniometry apparatus comprising an antenna array of several antennas, from several sets of calibration data measured in-flight by said goniometry apparatus, each associated with a measured angular position and comprising an amplitude datum and a phase datum measured by each antenna in said antenna array at said measured position.

Abstract: A method for detecting malicious connections from remote users into a computer network through Remote Desktop protocol via a computer having access to login logs of users. The method includes defining aspects, each divided into bins comprising a day of week aspect comprising n1 bins, a time of day aspect comprising n2 bins, a number of logins in a day aspect comprising n3 bins. The method includes defining a model based on the aspects and providing a score of log for each user; defining a baseline of log; applying the model on each user log to determine a production score of log and comparing the production score of log with respect to the baseline. The model includes calculating a probability density for each bin for each user, determining a weight for each aspect and calculating the score of log from the probability density weighted by the weight for each user.

Abstract: A method and a device for analyzing a consumption of resources in a computing infrastructure to predict a resource consumption anomaly on a computing device. The method includes determining a plurality of resource consumption modeling functions; determining a correlation between the resource consumption modeling functions; measuring a resource consumption by a measurement of a consumption value of a first resource; and predicting the resource consumption of the computing infrastructure. The predicting includes a calculation of a value of future consumption of a resource to be predicted from the consumption value of the first resource and from a previously calculated correlation between modeling functions.