Abstract:
The present invention relates to an ICN router (1), comprising a first cache layer (L1) and a second cache layer (L2), the first cache layer (L1) comprising a first content memory (11) and the second cache layer (L2) comprising a second content memory (21), the second content memory (21) having a higher capacity but a slower access speed than the first content memory (11), the router (1) being configured so that the first cache layer (L1) is adapted to fetch data from second cache layer (L2) when the router (1) is requested to output said data, characterized in that the first content memory (11) presents a first block size and the second content memory (21) presents a second block size, the second block size being higher that the first block size, the first content memory (11) comprising a swap area (110) through which the first content memory (11) is connected to the second content memory (21), the swap area (110) being adapted for individually serving blocks at the first block size as parts of blocks at the second size fetched from the second content memory (21).
Abstract:
The invention concerns a method for encrypting a binary data item characterised in that it comprises the steps consisting of: —generating a public key and a private key, the public key being a sparse matrix comprising m rows and n columns, m being greater than the number I of bits of the binary data item, I being an integer strictly greater than 1, and the private key being a set of I indexed sets of integers between 1 and m such that for each set, the sum of the elements of the rows of the sparse matrix indexed by the elements of a set is zero, and—generating a binary sequence b comprising m bits, such that b=Mx+e+y in which o x is a random binary vector, o e is a random binary noise vector, and o y is a linear encoding of data item c. The invention also concerns a method for calculating a Hamming distance on data encrypted by the method of encryption.
Abstract:
A method for training a machine learning system, including: based on at least one image dataset representing at least one portion of the hollow structure, calculating a signed distance field of each portion and calculating at least one geometrical parameter of each portion; generating a deployed in-use representation of the device by computing contact forces between the device and each portion based on the signed distance field and by applying these contact forces to a geometrical representation of the device; and training the machine learning system with each calculated geometrical parameter as an input and the corresponding deployed in-use representation as an associated target output, the obtained trained machine learning system being configured to receive as input at least one geometrical parameter and provide as output the deployed in-use representation of the device.
Abstract:
A method for learned image compression implemented in an autoencoder including a learnable encoder and a decoder, the method including: a) extracting from an image a latent space by the learnable encoder; b) quantizing the latent space by a quantizer to obtain a quantized latent space; c) entropy coding the quantized latent space by an entropy encoder to obtain a bitstream, wherein an entropy model used to encode the latent space is represented by a probability distribution; d) entropy decoding the bitstream by an entropy decoder to obtain an entropy decoded bitstream; e) feeding the entropy decoded bitstream to the decoder; f) recover a reconstructed image by the decoder; g) training the autoencoder via standard gradient descent of the backpropagated error gradient by finding learnable parameters of the learnable encoder and of the decoder that minimize a rate distortion cost function, wherein the entropy encoder is based on a differentiable formulation of a soft frequency counter.
Abstract:
A method for detecting at least one fault caused by a photoelectric or radiative effect in a non-volatile semiconductor memory, the memory including a plurality of memory cells (CM) containing MOS transistors, potentially floating-gate MOS transistors, each memory cell being located at the intersection of an elementary bit line (BLE) and of a word line (WL), the binary content of a memory cell being read out by detecting a read current (Ilecture) flowing through this memory cell during read-out after this memory cell has been selected by means of the elementary bit line and word line, in which method the potential presence of at least one fault during read-out or programming of a memory cell is detected by making a comparison between the total current flowing through the elementary bit line via which detection is performed, and a predefined threshold (Ialarm) representative of the presence of at least one fault.
Abstract:
A method for generating at least one information about the production of a handwritten, hand-affixed or printed trace on a surface. The method includes extracting several features describing the trace from at least one three-dimensional image of the trace, acquired by an imagery system. The method includes inputting the extracted features in a trained module to output the at least one information. The module has been trained beforehand with a plurality of previously-acquired three-dimensional images of traces and corresponding information related to the production of these traces.
Abstract:
A communication system having to an open radio access network architecture, the communication system includes a number (K) of user equipments configured to exchange messages through the communication system, the communication system comprising one or more radio unit and a distributed unit, each radio unit being connected to the distributed unit through a fronthaul link having a given capacity. The communication system comprises a coordination system being configured to coordinate the exchanges between the radio units of the system and the distributed unit, in response to a signal received by the radio units from a user equipment. The coordination system is configured to send a signalling message to each radio unit comprising data stream selection information, each radio unit comprising: a transformation unit configured to apply a transformation operation to the signal vector received by the radio unit, which provides a transformed vector, the transformation operation being defined to reduce the dimension of the received signal vector; a data stream selection unit configured to select a number of data streams corresponding to components of the transformed vector using the data stream selection information comprised in the signalling message, a quantizer configured to apply a quantization operation to the selected data streams, which provides quantized vectors, the radio unit being configured to send the quantized vectors to the distributed unit. The sum of the numbers of data streams selected at the radio units, over all the radio units of the communication system, is higher or equal to the product of the number of user equipments (K) and the number of antennas of a user equipment.
Abstract:
A decoder for decoding a signal received through a transmission channel represented by a channel matrix using a search sphere radius. The decoder comprises a radius determination device for determining a search sphere radius from a preliminary radius. The radius determination device is configured to: i. apply a machine learning algorithm to input data derived from the received signal, the channel matrix and a current radius, the current radius being initially set to the preliminary radius, which provides a current predicted number of lattice points associated with the current radius; ii. compare the current predicted number of lattice points to a given threshold; iii. update the current radius if the current predicted number of lattice points is strictly higher than the given threshold, the current radius being updated by applying a linear function to the current radius; Steps i to iii are iterated until a termination condition is satisfied, the termination condition being related to the current predicted number, the radius determination device being configured to set the search sphere radius to the current radius in response to the termination condition being satisfied.
Abstract:
A method for selecting features for the detection of a given brain condition, the method using a feature selector able to discriminate between at least two brain conditions, and using a plurality of electroencephalogram signals, relative to several brain electrodes and filtered on at least one frequency, the method comprising the following steps:
e) for each signal, computing at least one value quantifying brain activity for each brain electrode; f) for each signal, performing a thresholding of said computed quantifying values according to at least one threshold percentage, thus forming at least one group of thresholded values corresponding to each signal; g) using said feature selector to rank said thresholded values; and h) based on this ranking, selecting at least one feature vector comprising at least one electrode, and one frequency and/or one threshold percentage, and corresponding to the best ranked thresholded values for the detection of said given brain condition.
Abstract:
A decoder for determining an estimate of a vector of information symbols carried by optical signals propagating along a multi-core fiber in an optical fiber transmission channel according to two or more cores is provided. The decoder is implemented in an optical receiver. The optical signals are encoded using a space-time coding scheme and/or scrambled by at least one scrambling device arranged in the optical fiber transmission channel according to a predefined scrambling function. The decoder comprises a processing unit configured to adaptively: determine, in response to a temporal condition, one or more channel quality indicators from the optical signals; determine a decoding algorithm according to a target quality of service metric and on the one or more channel quality indicators; update the predefined scrambling function and/or the space-time coding scheme depending on the target quality of service metric and on the one or more channel quality indicators. The decoder further comprises a symbol estimation unit configured to determine an estimate of a vector of information symbols by applying the decoding algorithm to the optical signals.