Abrégé

A 3D building model generator has a server that constructs a 3D texture model for each floor in abuilding by extruding a 2D floor plan to 3D using user-inputted heights, and adding photos captured by a smartphone or mobile device as textures to image planes for surfaces in the 3D model. The server displays on the smartphone a floor-plan portion, or a virtual 3D display based on the camera orientation with a facing wall highlighted and confirmed by a smartphone user. The user moves mapping points overlaid upon the photo to wall corners to map the photo to the facing surface in the model. The user flags rooms and exits such as doors and elevators as walkable. The server stacks the 3D texture model for the floors and connects them into a walkable network ofthe rooms and exits that are flagged as walkable. Hashing removes duplicate floorplans.

Classes IPC  ?

• G06T 17/05 - Modèles géographiques

Abrégé

An automated magnetic endoscopy machine has a stationary disk that a person stands on that is surrounded by a rotating ring that has two telescoping poles, each having an electromagnet assembly with an actuator to raise and lower the electromagnet. Magnet current drivers adjust currents to the electromagnet to allow increased attraction to horizontally pull a swallowed capsule in the person's stomach. One actuator can move to a higher Z position than the other to pitch the capsule up, allowing imaging out of the horizontal plane. The rotating ring allows the electromagnets to rotate around a vertical axis. A sequence of rotational, Z, and radial/horizontal movements are performed by a control program that moves the capsule along paths in the stomach to capture images from cameras inside the capsule. The control program uses a laser in the capsule to map stomach walls before plotting paths through the stomach for imaging.

Classes IPC  ?

• A61B 1/00 - Instruments pour procéder à l'examen médical de l'intérieur des cavités ou des conduits du corps par inspection visuelle ou photographique, p. ex. endoscopesDispositions pour l'éclairage dans ces instruments
• A61B 1/04 - Instruments pour procéder à l'examen médical de l'intérieur des cavités ou des conduits du corps par inspection visuelle ou photographique, p. ex. endoscopesDispositions pour l'éclairage dans ces instruments combinés avec des dispositifs photographiques ou de télévision
• A61B 1/045 - Leur commande
• A61B 1/06 - Instruments pour procéder à l'examen médical de l'intérieur des cavités ou des conduits du corps par inspection visuelle ou photographique, p. ex. endoscopesDispositions pour l'éclairage dans ces instruments avec dispositifs d'éclairement

Abrégé

A resonant-based gate driving circuit for WBG power semiconductor devices is provided to suppress crosstalk in one leg configured power converters. The gate driving circuit comprises DC voltage source, first and second semiconductor switches, and a crosstalk suppressing circuit including: a first resonant inductor and a first resistor configured to form a path for charging an input capacitance of the WBG device up to the DC voltage source when a logic high control signal is generated from controller output and applied to the gate terminal of first and second semiconductor switches; a diode, a second resonance inductor, and a second resistor configured to form a path for discharging the input capacitance of WBG device, and to provide an adjustable negative gate-source turn-off voltage to the WBG device when a logic low control signal is generated from controller output and applied to the gate terminal of first and second semiconductor switches.

Classes IPC  ?

• H02M 1/088 - Circuits spécialement adaptés à la production d'une tension de commande pour les dispositifs à semi-conducteurs incorporés dans des convertisseurs statiques pour la commande simultanée de dispositifs à semi-conducteurs connectés en série ou en parallèle
• H02J 50/10 - Circuits ou systèmes pour l'alimentation ou la distribution sans fil d'énergie électrique utilisant un couplage inductif
• H02M 3/00 - Transformation d'une puissance d'entrée en courant continu en une puissance de sortie en courant continu
• H02M 3/335 - Transformation d'une puissance d'entrée en courant continu en une puissance de sortie en courant continu avec transformation intermédiaire en courant alternatif par convertisseurs statiques utilisant des tubes à décharge avec électrode de commande ou des dispositifs à semi-conducteurs avec électrodes de commande pour produire le courant alternatif intermédiaire utilisant des dispositifs du type triode ou transistor exigeant l'application continue d'un signal de commande utilisant uniquement des dispositifs à semi-conducteurs

Abrégé

A computer implemented method of generating a pseudo random sequence (PRS). The method comprises sub-dividing PRS generation operations into a plurality of PRS partitions. For each PRS partition, a PRS generation register value is determined based on an initial PRS value and a pre-computed PRS generation register advancement value. For each partition, the determined PRS generation register value is used to generate a PRS of an arbitrary or a predetermined length. The method includes transmitting the generated PRS to a computing module, device or system to perform a data processing function.

Classes IPC  ?

• G06F 7/58 - Générateurs de nombres aléatoires ou pseudo-aléatoires

Abrégé

A resonant-based gate driving circuit for WBG power devices is provided to suppress crosstalk in one leg configured power converters. The gate driving circuit comprises DC voltage source, first and second semiconductor switches, and a crosstalk suppressing circuit including: a first resonant inductor and a first resistor configured to form a path for charging an input capacitance of the WBG device up to the DC source voltage when a logic high control signal is generated from controller output and applied to the gate terminal of first and second semiconductor switches; a diode, a second resonance inductor, and a second resistor configured to form a path for discharging the input capacitance of WBG device, and to provide an adjustable negative gate-source turn-off voltage to the WBG device when a logic low control signal is generated from controller output and applied to the gate terminal of first and second semiconductor switches.

Classes IPC  ?

• H02M 1/08 - Circuits spécialement adaptés à la production d'une tension de commande pour les dispositifs à semi-conducteurs incorporés dans des convertisseurs statiques
• H02M 1/32 - Moyens pour protéger les convertisseurs autrement que par mise hors circuit automatique

Abrégé

A method of automatically determining sensor placement in a target environment. The method comprises receiving as inputs: a three-dimensional (3D) map of the target environment; a number of a plurality of sensors to be placed in the target environment; a set of placement configuration parameters for the plurality of sensors; and a set of constraints for the plurality of sensors in the target environment. The method includes, based on the received inputs, using a simulation platform to simulate, based on one or more defined conditions in the target environment, operation of the plurality of sensors to generate a dataset comprising simulated output data for the plurality of sensors; and using a Reinforcement Learning (RL) algorithm to determine from the dataset comprising simulated output data for the plurality of sensors an optimized or at least an improved set of placement configuration parameters for the plurality of sensors.

Classes IPC  ?

• G01S 17/931 - Systèmes lidar, spécialement adaptés pour des applications spécifiques pour prévenir les collisions de véhicules terrestres

Abrégé

An image-guided diffusion network has two Convolution Neural Networks (CNNs). A RGB image and an IR image are concatenated with a Gaussian noise image and input to a denoising neural network that merges information from the RGB and IR images as noise is removed over many iterations. Then an enhancement neural network up-samples for Super Resolution (SR) and convolutes to generate a condition vector that controls Global Feature Modulation (GFM) at three convolution layers to generate a SRGFM enhanced fusion image. Timesteps are embedded using adaptive group normalization blocks within Adaptive Bottleneck Residual (ABR) blocks in the denoising network, which is a UNet having many levels of ABRs, and in the enhancement network before feature modulation. Global image features are detected by triple convoluting the image input to the enhancement network to generate the condition vector that controls feature modulation blocks at three layers of convolution.

Classes IPC  ?

• G06T 5/50 - Amélioration ou restauration d'image utilisant plusieurs images, p. ex. moyenne ou soustraction
• G06T 3/4053 - Changement d'échelle d’images complètes ou de parties d’image, p. ex. agrandissement ou rétrécissement basé sur la super-résolution, c.-à-d. où la résolution de l’image obtenue est plus élevée que la résolution du capteur
• G06T 5/70 - DébruitageLissage
• G06V 10/42 - Extraction de caractéristiques globales par l’analyse du motif entier, p. ex. utilisant des transformations dans le domaine de fréquence ou d’autocorrélation
• G06V 10/771 - Sélection de caractéristiques, p. ex. sélection des caractéristiques représentatives à partir d’un espace multidimensionnel de caractéristiques
• G06V 10/80 - Fusion, c.-à-d. combinaison des données de diverses sources au niveau du capteur, du prétraitement, de l’extraction des caractéristiques ou de la classification

Abrégé

Anti-counterfeiting is benefited by integrating both optical and digital encoding-decoding approaches for spoof protection, e.g., in print anti-spoofing. An optical-digital encoding-decoding system uses an encoded medium, such as a security label, to display images encoded with digital data, and a decoding device to decode or decrypt the digital data for achieving stronger authentication in anti-counterfeiting or other security-related purposes. The images are encoded into resonant waveguide gratings (RWGs) in the encoded medium, enabling angle multiplexing of the displayed images and addressing different secrecy requirements in optically handling different groups of security-related data. Furthermore, aperiodic diffraction gratings instead of periodic ones are used in RWGs for selected images intended to be viewed by users, broadening beamwidths of outgoing light beams generated by these RWGs to allow the selected images to be more conveniently viewed by the users over a wider range of angle.

Classes IPC  ?

• G06F 21/60 - Protection de données
• G02B 5/18 - Grilles de diffraction
• G02B 6/34 - Moyens de couplage optique utilisant des prismes ou des réseaux

Abrégé

Anti-counterfeiting is benefited by integrating both optical and digital encoding-decoding approaches for spoof protection, e.g., in print anti-spoofing. An optical-digital encoding-decoding system uses an encoded medium, such as a security label, to display images encoded with digital data, and a decoding device to decode or decrypt the digital data for achieving stronger authentication in anti-counterfeiting or other security-related purposes. The images are encoded into resonant waveguide gratings (RWGs) in the encoded medium, enabling angle multiplexing of the displayed images and addressing different secrecy requirements in optically handling different groups of security-related data. Furthermore, aperiodic diffraction gratings instead of periodic ones are used in RWGs for selected images intended to be viewed by users, broadening beamwidths of outgoing light beams generated by these RWGs to allow the selected images to be more conveniently viewed by the users over a wider range of angle.

Classes IPC  ?

• G06N 3/067 - Réalisation physique, c.-à-d. mise en œuvre matérielle de réseaux neuronaux, de neurones ou de parties de neurone utilisant des moyens optiques

Abrégé

A LiDAR apparatus with an selective reflecting device is provided. The LiDAR apparatus comprises a laser source, an optical turning device, and a selective reflecting device. The selective reflecting device comprises a convex surface, and a selective reflecting layer disposed on the convex surface. The laser source is configured to provide a light beam. The optical turning device is configured to accept the light beam and to direct it towards the selective reflecting device. The selective reflecting layer is configured to reflect the light beam, and to allow a visible light to pass through the selective reflecting layer. The optical turning device is configured to turn the light beam and to change a position on the selective reflecting layer on the convex surface that is illuminated by the light beam.

Classes IPC  ?

• G01S 7/481 - Caractéristiques de structure, p. ex. agencements d'éléments optiques
• G01S 17/08 - Systèmes déterminant les données relatives à la position d'une cible pour mesurer la distance uniquement
• G01S 17/931 - Systèmes lidar, spécialement adaptés pour des applications spécifiques pour prévenir les collisions de véhicules terrestres

Abrégé

A LiDAR apparatus with an selective reflecting device is provided. The LiDAR apparatus comprises a laser source, an optical turning device, and a selective reflecting device. The selective reflecting device comprises a convex surface, and a selective reflecting layer disposed on the convex surface. The laser source is configured to provide a light beam. The optical turning device is configured to accept the light beam and to direct it towards the selective reflecting device. The selective reflecting layer is configured to reflect the light beam, and to allow a visible light to pass through the selective reflecting layer. The optical turning device is configured to turn the light beam and to change a position on the selective reflecting layer on the convex surface that is illuminated by the light beam.

Classes IPC  ?

• G01S 7/481 - Caractéristiques de structure, p. ex. agencements d'éléments optiques

Abrégé

A speed bridge which provides high verification productivity in a hardware emulation system by allowing for time-efficient communication between a host/server and a device under test is disclosed. The speed bridge emulates the host to the device and the device to the host simultaneously while being in communication with both. When the message/response between the host and the device is fixed, the virtual host communicates with the virtual device. When the message/response requires physical interaction, the speed bridge passes the message/response between the host/server and the device.

Classes IPC  ?

• G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation

Abrégé

A speed bridge which provides high verification productivity in a hardware emulation system by allowing for time-efficient communication between a host/server and a device under test is disclosed. The speed bridge emulates the host to the device and the device to the host simultaneously while being in communication with both. When the message/response between the host and the device is fixed, the virtual host communicates with the virtual device. When the message/response requires physical interaction, the speed bridge passes the message/response between the host/server and the device.

Classes IPC  ?

• G06F 13/10 - Commande par programme pour dispositifs périphériques
• G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation

Abrégé

A method of estimating local oscillator leakage (LOL) for a radio frequency (RF) signal transmitter. The method comprises generating a transmitter wideband baseband signal (s(t)) with a direct current (DC) voltage element of the transmitter wideband baseband signal (s(t)) removed or blocked and an average of the transmitter wideband baseband signal (s(t)) set to zero. The method includes processing said transmitter wideband baseband signal (s(t)) to form a RF signal; processing the RF signal to obtain a receiver baseband signal (y(t)); and determining a magnitude of an average of the receiver baseband signal (y(t)) as comprising a magnitude of the transmitter DC offset.

Classes IPC  ?

• H04B 17/15 - Tests de performance

Abrégé

An AI-based system for the generation, evaluation, and prediction of performance of banner ads for presentation to specific customers or types of customers. A data set of existing banner ads, ad materials, and design and marketing parameters is used to generate a graph-based model. The graph-based model is used to generate original banner ads, which are then evaluated by a machine learning model, which assigns them scores. The highest-scoring banner ads are then presented to customers. The invention can also use a genetic algorithm in combination with iterative evaluation and generation to diversify design and choose the highest ranked banner ads.

Classes IPC  ?

• G06Q 30/0241 - Publicités
• G06Q 30/0242 - Détermination de l’efficacité des publicités

Abrégé

A method for processing multiple image data sets, each image data set generated by a different ultrasound frequency emitter, to obtain a single merged image data set for use to display a single merged image. The method can also include steps to account for non-ideal alignment between the different ultrasound frequency emitters.

Classes IPC  ?

• A61B 8/08 - Applications cliniques
• A61B 8/00 - Diagnostic utilisant des ondes ultrasonores, sonores ou infrasonores

Abrégé

An AI-based system that uses data sets of existing banner ads, advertising materials, and design and marketing parameters, based on image algorithms and technology, to generate, evaluate, and predict performance of banner ads and present them to specific customers or specific types of customers. The graph-based model is used to generate original banner ads, which are then evaluated by a machine learning model, which assigns them scores. The highest-scoring banner ads are then presented to customers. A genetic algorithm in combination with iterative evaluation and generation are used to diversify design and choose the highest ranked banner ads.

Classes IPC  ?

• G06Q 30/0241 - Publicités
• G06N 3/126 - Algorithmes évolutionnaires, p. ex. algorithmes génétiques ou programmation génétique
• G06Q 30/0251 - Publicités ciblées
• G06N 20/20 - Techniques d’ensemble en apprentissage automatique
• G06N 5/022 - Ingénierie de la connaissanceAcquisition de la connaissance
• G06F 18/2433 - Perspective d'une seule classe, p. ex. une classification "une contre toutes"Détection de nouveautéDétection de valeurs aberrantes

Abrégé

A method for processing multiple image data sets, each image data set generated by a different ultrasound frequency emitter, to obtain a single merged image data set for use to display a single merged image. The method can also include steps to account for non-ideal alignment between the different ultrasound frequency emitters.

Classes IPC  ?

• A61B 8/08 - Applications cliniques
• G06T 1/20 - Architectures de processeursConfiguration de processeurs p. ex. configuration en pipeline

Abrégé

A swallowable capsule has a primary magnet along a long axis that aligns between movable electromagnets in a magnetic endoscopy machine. A flip magnet is orthogonal to the long axis. The capsule is rolled around the long axis to flip orientation of a side camera on a side of the capsule. An external base electromagnet below the patient's feet is energized to roll the capsule. The base magnet acts on the flip magnet but not on the orthogonal primary magnet when the long axis is orthogonal to a magnetic axis of the base electromagnet. Most components such as a controller, the side camera, a side laser, batteries, and an antenna, are mounted to a long Printed Circuit Board (PCB) along the long axis, while a front camera and laser are mounted to a front PCB that is mounted orthogonally to a front edge of the long PCB.

Classes IPC  ?

• A61B 1/04 - Instruments pour procéder à l'examen médical de l'intérieur des cavités ou des conduits du corps par inspection visuelle ou photographique, p. ex. endoscopesDispositions pour l'éclairage dans ces instruments combinés avec des dispositifs photographiques ou de télévision
• A61B 1/00 - Instruments pour procéder à l'examen médical de l'intérieur des cavités ou des conduits du corps par inspection visuelle ou photographique, p. ex. endoscopesDispositions pour l'éclairage dans ces instruments
• A61B 1/06 - Instruments pour procéder à l'examen médical de l'intérieur des cavités ou des conduits du corps par inspection visuelle ou photographique, p. ex. endoscopesDispositions pour l'éclairage dans ces instruments avec dispositifs d'éclairement

Abrégé

An apparatus for intrusion detection and prevention of cyber threat intelligence is provided. The apparatus includes a feature extraction model, a feature selection model, a flow-based intrusion detection module, a packet-based intrusion detection module, and an IPM. The feature extraction model is configured to parse packets from network raw packet data into sessions as a network flow dataset. The feature selection model is configured to select flow-based features from the network flow dataset to generate network flow meta. The flow-based intrusion detection module is configured to generate flow-based labels. The packet-based intrusion detection module is configured to generate packet-based labels. The IPM is configured to perform intrusion analysis according to the flow-based labels and the packet-based labels so as to generate IPM rules for intrusion detection and prevention, thereby identifying and processing the network raw packet data.

Classes IPC  ?

• H04L 9/40 - Protocoles réseaux de sécurité

Abrégé

An apparatus for intrusion detection and prevention of cyber threat intelligence is provided. The apparatus includes a feature extraction model, a feature selection model, a flow-based intrusion detection module, a packet-based intrusion detection module, and an IPM. The feature extraction model is configured to parse packets from network raw packet data into sessions as a network flow dataset. The feature selection model is configured to select flow-based features from the network flow dataset to generate network flow meta. The flow-based intrusion detection module is configured to generate flow-based labels. The packet-based intrusion detection module is configured to generate packet-based labels. The IPM is configured to perform intrusion analysis according to the flow-based labels and the packet-based labels so as to generate IPM rules for intrusion detection and prevention, thereby identifying and processing the network raw packet data.

Classes IPC  ?

• H04L 9/40 - Protocoles réseaux de sécurité

Abrégé

Shoot-through current flows when a pull-up transistor and a pull-down transistor in series both turn ON at the same time, such as due to noise. The transistor that should be OFF has an OFF drain-source voltage that is high when the other transistor is ON, but quickly falls when the OFF transistor erroneously turns on. A shoot-through protection circuit compares the OFF drain-source voltage of the OFF transistor to a reference voltage. When the OFF drain-source voltage falls below the reference voltage, a fault is signaled. The fault signal immediately disables the ON transistor by driving its gate inactive (low) to stop the shoot-through current. The reference voltage may be a fraction of the power voltage, such as 30%of a 400-volt input power bus, providing over 100 volts noise immunity, preventing false triggering yet immediately blocking current when the reference voltage is passed without waiting for a blanking period.

Classes IPC  ?

• H03K 17/081 - Modifications pour protéger le circuit de commutation contre la surintensité ou la surtension sans réaction du circuit de sortie vers le circuit de commande

Abrégé

Shoot-through current flows when a pull-up transistor and a pull-down transistor in series both turn ON at the same time, such as due to noise. The transistor that should be OFF has an OFF drain-source voltage that is high when the other transistor is ON, but quickly falls when the OFF transistor erroneously turns on. A shoot-through protection circuit compares the OFF drain-source voltage of the OFF transistor to a reference voltage. When the OFF drain-source voltage falls below the reference voltage, a fault is signaled. The fault signal immediately disables the ON transistor by driving its gate inactive (low) to stop the shoot-through current. The reference voltage may be a fraction of the power voltage, such as 30% of a 400-volt input power bus, providing over 100 volts noise immunity, preventing false triggering yet immediately blocking current when the reference voltage is passed without waiting for a blanking period.

Classes IPC  ?

• H03K 17/08 - Modifications pour protéger le circuit de commutation contre la surintensité ou la surtension

Abrégé

The present invention provides an apparatus for producing labelled cursive handwritten text samples with context style variability, and method of training and using the same. The apparatus comprises: a word embedding units configured for encoding an input text to obtain an input text word embedding; a word embedding unit configured for encoding a handwriting context style description into a context style description embedding; a transformer configured for transforming the context style description embedding to obtain a handwriting context style feature embedding; a feature embedding combiner configured for combining the handwriting context style feature embedding and the input text word embeddings to form a combined feature embedding; a generator configured for generating a synthetic image containing characters occurred in the input text with the handwriting context style defined in the handwriting context style description and context style variability introduced by the generator.

Classes IPC  ?

• G06V 30/302 - Images contenant des caractères pour discriminer entre l’accès humain ou automatisé à l’ordinateur
• G06F 40/169 - Annotation, p. ex. données de commentaires ou notes de bas de page
• G06V 30/19 - Reconnaissance utilisant des moyens électroniques

Abrégé

The present invention provides an apparatus for producing labelled cursive handwritten text samples with context style variability, and method of training and using the same. The apparatus comprises: a word embedding units configured for encoding an input text to obtain an input text word embedding; a word embedding unit configured for encoding a handwriting context style description into a context style description embedding; a transformer configured for transforming the context style description embedding to obtain a handwriting context style feature embedding; a feature embedding combiner configured for combining the handwriting context style feature embedding and the input text word embeddings to form a combined feature embedding; a generator configured for generating a synthetic image containing characters occurred in the input text with the handwriting context style defined in the handwriting context style description and context style variability introduced by the generator.

Classes IPC  ?

• G06V 30/226 - Reconnaissance de caractères caractérisés par le type d’écriture de l’écriture cursive
• G06V 30/18 - Extraction d’éléments ou de caractéristiques de l’image
• G06V 30/146 - Alignement ou centrage du capteur d’image ou du champ d’image
• G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
• G06N 3/094 - Apprentissage antagoniste

Abrégé

A method for processing electronic documents, comprising: receiving an electronic document; recognizing one or more content components in the electronic document; identifying a content type for each of the recognized content components; creating, by a layer separator, one or more logical layers from the recognized content components such that each of the logical layer contains only the content components of the same content type; and invoking a content-type specific content handler for each of the logical layers created. The layer separator comprises a machine learning (ML) model based on a modified U-Net convolutional neural network and trained to classify the content types of the content components. The modified U-Net CNN is improved over traditional U-Net CNN with transformers at each layer to achieve high recovery rate.

Classes IPC  ?

• G06V 30/416 - Extraction de la structure logique, p. ex. chapitres, sections ou numéros de pageIdentification des éléments de document, p. ex. des auteurs
• G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
• G06V 30/22 - Reconnaissance de caractères caractérisés par le type d’écriture
• G06V 30/413 - Classification de contenu, p. ex. de textes, de photographies ou de tableaux

Abrégé

A method for processing electronic documents, comprising: receiving an electronic document; recognizing one or more content components in the electronic document; identifying a content type for each of the recognized content components; creating, by a layer separator, one or more logical layers from the recognized content components such that each of the logical layer contains only the content components of the same content type; and invoking a content-type specific content handler for each of the logical layers created. The layer separator comprises a machine learning (ML) model based on a modified U-Net convolutional neural network and trained to classify the content types of the content components. The modified U-Net CNN is improved over traditional U-Net CNN with transformers at each layer to achieve high recovery rate.

Classes IPC  ?

• G06V 30/413 - Classification de contenu, p. ex. de textes, de photographies ou de tableaux
• G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux

Abrégé

An apparatus for virtual avatar generation is provided, including a face encoder, a face fusion engine, a voice encoder, and a voice fusion engine. The face encoder extracts first facial features from the first facial image and then encodes they into M first facial feature vectors and extracts second facial features from the second facial image and then encodes they into M second facial feature vectors. The face fusion engine generates a facial fused feature vector from the facial feature vectors, thereby generating a fused image. The voice encoder extracts first voice features from the first audio clip and then encodes they into N first voice feature vectors and extracts second voice features from the second audio clip and then encodes they into N second voice feature vectors. The voice fusion engine synthesizes a voice fused feature vector from the voice feature vectors, thereby generating a fused voice.

Classes IPC  ?

• G06T 17/00 - Modélisation tridimensionnelle [3D] pour infographie
• G06F 3/04855 - Interaction avec des barres de défilement
• G06T 5/50 - Amélioration ou restauration d'image utilisant plusieurs images, p. ex. moyenne ou soustraction
• G06T 13/40 - Animation tridimensionnelle [3D] de personnages, p. ex. d’êtres humains, d’animaux ou d’êtres virtuels
• G06V 40/16 - Visages humains, p. ex. parties du visage, croquis ou expressions
• G10L 15/02 - Extraction de caractéristiques pour la reconnaissance de la paroleSélection d'unités de reconnaissance

Abrégé

Systems and methods which provide single nanostructure-integrated metalens (110) configurations implementing light focusing functionality are described. A single nanostructure-integrated metalens (110) may comprise an optical substrate (111) having a preconfigured mapping of integrated nanostructures (112) providing metasurfaces for modulating the behaviors of electromagnetic waves to implement a thin, flat lens. A period distance for the nanostructures (112), a height of the nanostructures (112), and a quantization for lateral sizes of the nanostructures (112) may be selected for a particular single nanostructure-integrated metalens (110) configuration. One or more phase maps configured for light focusing may be computed with respect to one or more design wavelengths selected for focusing. The consolidated phase retardation requirements of the one or more phase maps may be satisfied by a preconfigured mapping which defines the phase distribution for the nanostructures (112) of a single nanostructure-integrated metalens (110) implementation.

Classes IPC  ?

• G02B 1/00 - Éléments optiques caractérisés par la substance dont ils sont faitsRevêtements optiques pour éléments optiques

Abrégé

An apparatus for virtual avatar generation is provided, including a face encoder, a face fusion engine, a voice encoder, and a voice fusion engine. The face encoder extracts first facial features from the first facial image and then encodes they into M first facial feature vectors and extracts second facial features from the second facial image and then encodes they into M second facial feature vectors. The face fusion engine generates a facial fused feature vector from the facial feature vectors, thereby generating a fused image. The voice encoder extracts first voice features from the first audio clip and then encodes they into N first voice feature vectors and extracts second voice features from the second audio clip and then encodes they into N second voice feature vectors. The voice fusion engine synthesizes a voice fused feature vector from the voice feature vectors, thereby generating a fused voice.

Classes IPC  ?

• G06V 40/16 - Visages humains, p. ex. parties du visage, croquis ou expressions

Abrégé

A 3D building model generator has a server that constructs a 3D texture model for each floor in a building by extruding a 2D floor plan to 3D using user-inputted heights, and adding photos captured by a smartphone or mobile device as textures to image planes for surfaces in the 3D model. The server displays on the smartphone a floor-plan portion, or a virtual 3D display based on the camera orientation with a facing wall highlighted and confirmed by a smartphone user. The user moves mapping points overlaid upon the photo to wall corners to map the photo to the facing surface in the model. The user flags rooms and exits such as doors and elevators as walkable. The server stacks the 3D texture model for the floors and connects them into a walkable network of the rooms and exits that are flagged as walkable. Hashing removes duplicate floorplans.

Classes IPC  ?

• G06T 17/00 - Modélisation tridimensionnelle [3D] pour infographie
• H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système

Abrégé

Reagents A, B, C are added to an electrolyte bath for co-depositing tin-bismuth alloys (Sn—Bi). Reagent A is a larger acid molecule that binds to Bi3+ ions while reagent B is a small molecule that binds to the Bi3+ ions in spaces between the reagent A molecules. Reagents A and B reduce the standard electrode potential difference of Sn and Bi to permit co-deposition rates that yield a Sn—Bi alloy of 30-70% Bi by weight, around the 58% eutectic, with an alloy melting point below 180° C. for use as a low-temperature solder. Reagent C has a hydrophilic end that attaches to the electrode surface and a hydrophobic tail that is an aliphatic chain that attracts hydrogen gas, removing H2 gas from the electrode surface. Reagent C improves alloy microstructure by removing H2 gas generated at the cathode that can block Bi3+ ions from uniformly depositing on the surface.

Classes IPC  ?

• C25D 3/32 - Dépôt électrochimiqueBains utilisés à partir de solutions d'étain caractérisé par les constituants organiques utilisés pour le bain
• C25D 3/60 - Dépôt électrochimiqueBains utilisés à partir de solutions d'alliages contenant plus de 50% en poids d'étain
• C25D 17/14 - Électrodes pour dépôt au tampon

Abrégé

5GSTSNDS-TTDS-TTDS-TT to synchronize the DS-TT module with the TSN GM.

Classes IPC  ?

• H04W 56/00 - Dispositions de synchronisation

Abrégé

A method for position and/or deviation correction of a moving object in a simultaneous localization and mapping (SLAM) environment. The method comprises receiving at the moving object point cloud data for an area associated with the moving object from a sensor located at a fixed location. A processor of the moving object performs the steps of: transforming the received point cloud data to a coordinate system of the moving object (16); matching the transformed point cloud data with point cloud data generated by a sensor at the moving object for the area associated with the moving object (17); and using the matched point cloud data to determine a corrected position and/or deviation of the moving object within a selected coordinate system (18).

Classes IPC  ?

• G01C 25/00 - Fabrication, étalonnage, nettoyage ou réparation des instruments ou des dispositifs mentionnés dans les autres groupes de la présente sous-classe
• G01C 21/26 - NavigationInstruments de navigation non prévus dans les groupes spécialement adaptés pour la navigation dans un réseau routier
• G01C 21/00 - NavigationInstruments de navigation non prévus dans les groupes
• G01S 17/89 - Systèmes lidar, spécialement adaptés pour des applications spécifiques pour la cartographie ou l'imagerie
• G01S 7/48 - Détails des systèmes correspondant aux groupes , , de systèmes selon le groupe

Abrégé

A power-converter module has a switching Printed Circuit Board (PCB) with power transistors generating heat. Ground, an input power supply, and an output power supply to the power transistors connect through metal traces on the switching PCB directly to interposer heat sinks that are soldered to the switching PCB. Copper bars attached to the bottoms of interposer heat sinks fit in holes in a system PCB to make connections. The metal traces and interposer heat sinks carry supply or ground currents and heat away from the power transistors. These power and ground currents continue from the interposer heat sinks through the copper bars to the system PCB. An interposer PCB has soler pads and solder balls to carry control signals from the system PCB to the switching PCB, bypassing the interposer heat sinks. Copper bars can be sintered, soldered, or welded to or integral with the interposer heat sinks.

Classes IPC  ?

• H05K 1/02 - Circuits imprimés Détails
• H05K 1/18 - Circuits imprimés associés structurellement à des composants électriques non imprimés
• H05K 1/11 - Éléments imprimés pour réaliser des connexions électriques avec ou entre des circuits imprimés
• H01L 23/367 - Refroidissement facilité par la forme du dispositif
• H02M 3/07 - Transformation d'une puissance d'entrée en courant continu en une puissance de sortie en courant continu sans transformation intermédiaire en courant alternatif par convertisseurs statiques utilisant des résistances ou des capacités, p. ex. diviseur de tension utilisant des capacités chargées et déchargées alternativement par des dispositifs à semi-conducteurs avec électrode de commande
• H02M 1/00 - Détails d'appareils pour transformation
• H02M 1/14 - Dispositions de réduction des ondulations d'une entrée ou d'une sortie en courant continu

Abrégé

Reagents A, B, C are added to an electrolyte bath for co-depositing tin-bismuth alloys (Sn-Bi). Reagent A is a larger acid molecule that binds to Bi3+ions while reagent B is a small molecule that binds to the Bi3+222 gas generated at the cathode that can block Bi3+ions from uniformly depositing on the surface.

Classes IPC  ?

• C25D 3/56 - Dépôt électrochimiqueBains utilisés à partir de solutions d'alliages
• C25D 3/60 - Dépôt électrochimiqueBains utilisés à partir de solutions d'alliages contenant plus de 50% en poids d'étain
• C25D 7/00 - Dépôt électrochimique caractérisé par l'objet à revêtir

Abrégé

A method for analyzing environmental sounds to identify repeating noises due to power equipment for purposes of controlling noise pollution is disclosed. Ambient sounds are sampled with microphones and the resulting data analyzed by an edge computing device. The samples are compared to stored data with a convolutional neural network by the edge computing device which also performs pitch shifting and cycle shifting to reduce false negatives. Positive results are reported via LoRa and/or 4G to a cloud platform and/or backend server.

Classes IPC  ?

• H04W 24/10 - Planification des comptes-rendus de mesures

Abrégé

A Hybrid TEE device allows a Trusted Execution Environment (TEE) by incorporating hardware comprising a Cache Purging Controller, a Memory Isolation Gateway, and a Memory Clean Up into a System on a Chip device, a general purpose computing device, or a special purpose or proprietary computing or electronic device. The addition of the hardware enables a method of protecting the Trusted Execution Environment and thus reducing vulnerability to malicious software or other program code.

Classes IPC  ?

• G06F 21/79 - Protection de composants spécifiques internes ou périphériques, où la protection d'un composant mène à la protection de tout le calculateur pour assurer la sécurité du stockage de données dans les supports de stockage à semi-conducteurs, p. ex. les mémoires adressables directement
• G06F 21/53 - Contrôle des utilisateurs, des programmes ou des dispositifs de préservation de l’intégrité des plates-formes, p. ex. des processeurs, des micrologiciels ou des systèmes d’exploitation au stade de l’exécution du programme, p. ex. intégrité de la pile, débordement de tampon ou prévention d'effacement involontaire de données par exécution dans un environnement restreint, p. ex. "boîte à sable" ou machine virtuelle sécurisée
• G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité

Abrégé

A Hybrid TEE device allows a Trusted Execution Environment (TEE) by incorporating hardware comprising a Cache Purging Controller, aMemory Isolation Gateway, and a Memory Clean Up into a System on a Chip device, ageneral purpose computing device, or a special purpose or proprietary computing or electronic device. The addition of the hardware enables a method of protecting the Trusted Execution Environment and thus reducing vulnerability to malicious software or other program code.

Classes IPC  ?

• G06F 21/71 - Protection de composants spécifiques internes ou périphériques, où la protection d'un composant mène à la protection de tout le calculateur pour assurer la sécurité du calcul ou du traitement de l’information

Abrégé

The present invention provides a method for achieving high availability of stream control transport protocol (SCTP) connection in a microservice system. The microservice system comprises at least one access network and a core network. The access network includes at least one base station comprising at least one SCTP peer. The core network includes at least one non-SCTP-capable microservice instance acting as a SCTP service client, multiple SCTP-capable microservice instances, aservice node manager and a service delegator. The method comprises: tagging each of the SCTP-capable microservice instances with a SCTP-service label; periodically scanning the microservice system, by the service node manager, to detect alive SCTP-capable microservice instances; dynamically maintaining, by the service node manager, abackend list of alive SCTP-capable microservice instances; and selecting, by the service delegator, an alive SCTP service instance from the maintained backend list according to a selection rule whenever a SCTP service request is received.

Classes IPC  ?

• H04W 24/04 - Configurations pour maintenir l'état de fonctionnement

Abrégé

An apparatus for analysing and monitoring a network flow for cyber threat intelligence is provided. The apparatus includes a feature selection model, a feature classification model, a threat computation model, a cyber threat intelligence engine, and a monitoring system. The feature selection model is configured to select flow-based features from a dataset in a network flow to generate network flow meta. The feature classification model is configured to analysis the flow-based features of the network flow meta to generate classified features. The threat computation model is configured to predict the threat features from the classified features using a swappable prediction model. The cyber threat intelligence engine is configured to collect and combine the flow-based features, the classified features, and the threat features to form one or more cyber threat joint features. The monitoring system is configured to output the cyber threat joint features.

Classes IPC  ?

• H04L 9/40 - Protocoles réseaux de sécurité
• H04L 41/14 - Analyse ou conception de réseau

Abrégé

An apparatus for analysing and monitoring a network flow for cyber threat intelligence is provided. The apparatus includes a feature selection model, a feature classification model, a threat computation model, a cyber threat intelligence engine, and a monitoring system. The feature selection model is configured to select flow-based features from a dataset in a network flow to generate network flow meta. The feature classification model is configured to analysis the flow-based features of the network flow meta to generate classified features. The threat computation model is configured to predict the threat features from the classified features using a swappable prediction model. The cyber threat intelligence engine is configured to collect and combine the flow-based features, the classified features, and the threat features to form one or more cyber threat joint features. The monitoring system is configured to output the cyber threat joint features.

Classes IPC  ?

• H04L 9/40 - Protocoles réseaux de sécurité

Abrégé

A method of aligning and overlaying an AR virtual object in an electronic 3D viewing environment, comprising: receiving a motion comprising: a surrounding real-world scene image containing the real-world object captured by a camera of the electronic 3D viewing environment, and a camera real-world pose; recognizing a reference feature for aligning the virtual object to the real-world object; recording the motion and its corresponding reference feature; estimating a real-world object pose using the camera real-world pose and the reference feature; refining the estimated real-world object pose by pose estimation refinement by features and pose estimation refinement by images; and rendering the virtual object according to the estimated and refined real-world object pose in the 3D viewing environment.

Classes IPC  ?

• G06T 19/00 - Transformation de modèles ou d'images tridimensionnels [3D] pour infographie
• G06T 19/20 - Édition d'images tridimensionnelles [3D], p. ex. modification de formes ou de couleurs, alignement d'objets ou positionnements de parties
• G06V 10/74 - Appariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques
• G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux

Abrégé

A method of aligning and overlaying an AR virtual object in an electronic 3D viewing environment, comprising: receiving a motion comprising: a surrounding real-world scene image containing the real-world object captured by a camera of the electronic 3D viewing environment, and a camera real-world pose; recognizing a reference feature for aligning the virtual object to the real-world object; recording the motion and its corresponding reference feature; estimating a real-world object pose using the camera real-world pose and the reference feature; refining the estimated real-world object pose by pose estimation refinement by features and pose estimation refinement by images; and rendering the virtual object according to the estimated and refined real-world object pose in the 3D viewing environment.

Classes IPC  ?

• G06T 19/00 - Transformation de modèles ou d'images tridimensionnels [3D] pour infographie

Abrégé

The present disclosure proposes a method used by a receiver for facilitating de-rate matching of bits of symbols formed after a rate matching procedure from a transmitter, wherein the transmitter selected Z bits from channel-coded bits, and then generated E bits by concatenation of the Z bits and their copies for the rate matching procedure. The method comprises: demodulating the symbols to obtain E soft bits corresponding to the E bits; zeroing values at Z consecutive locations of a memory, wherein the Z consecutive locations correspond to bit positions of the Z bits; writing the E soft bits into a buffer device; for each soft bit of the E soft bits in the buffer device, directly adding value of the soft bit and value from a location of the Z consecutive locations and storing result of the addition back into the location, wherein a bit in the E bits corresponding to the soft bit is a bit in the Z bits corresponding to the location or a copy of the bit in the Z bits; and restoring the Z bits from the final results at the Z consecutive locations. The method facilitates the de-rate matching by reducing its memory usage and processing latency.

Classes IPC  ?

• H04L 1/00 - Dispositions pour détecter ou empêcher les erreurs dans l'information reçue
• H04W 28/22 - Négociation du débit de transmission

Abrégé

The present invention provides a method and a system for remote imaging of explosive gases in an area. The method comprises: illuminating the area with a light source having a uniform light intensity distribution over an infrared wavelength range (S110); acquiring images of the illuminated area with an image sensor through gas detection filters having bandpass central wavelength corresponding to absorption curves of target gases respectively (S120); determining existence of the target gases based on the acquired images (S130); predicting distribution of gas concertation for existing target gases respectively by using a non-linear prediction model (S140); and constructing gas distribution images of the area based on the predicted distribution of gas concertation (S150). The present invention can recognize different gases with overlapping absorption curves and provide more accurate prediction of gas concentrations.

Classes IPC  ?

• G01N 21/3504 - CouleurPropriétés spectrales, c.-à-d. comparaison de l'effet du matériau sur la lumière pour plusieurs longueurs d'ondes ou plusieurs bandes de longueurs d'ondes différentes en recherchant l'effet relatif du matériau pour les longueurs d'ondes caractéristiques d'éléments ou de molécules spécifiques, p. ex. spectrométrie d'absorption atomique en utilisant la lumière infrarouge pour l'analyse des gaz, p. ex. analyse de mélanges de gaz

Abrégé

The present invention provides a method and a system for remote imaging of explosive gases in an area. The method comprises: illuminating the area with a light source having a uniform light intensity distribution over an infrared wavelength range; acquiring images of the illuminated area with an image sensor through gas detection filters having bandpass central wavelength corresponding to absorption curves of target gases respectively; determining existence of the target gases based on the acquired images; predicting distribution of gas concertation for existing target gases respectively by using a non-linear prediction model; and constructing gas distribution images of the area based on the predicted distribution of gas concertation. The present invention can recognize different gases with overlapping absorption curves and provide more accurate prediction of gas concentrations.

Classes IPC  ?

• G01N 21/3504 - CouleurPropriétés spectrales, c.-à-d. comparaison de l'effet du matériau sur la lumière pour plusieurs longueurs d'ondes ou plusieurs bandes de longueurs d'ondes différentes en recherchant l'effet relatif du matériau pour les longueurs d'ondes caractéristiques d'éléments ou de molécules spécifiques, p. ex. spectrométrie d'absorption atomique en utilisant la lumière infrarouge pour l'analyse des gaz, p. ex. analyse de mélanges de gaz
• H04N 23/20 - Caméras ou modules de caméras comprenant des capteurs d'images électroniquesLeur commande pour générer des signaux d'image uniquement à partir d'un rayonnement infrarouge
• H04N 23/56 - Caméras ou modules de caméras comprenant des capteurs d'images électroniquesLeur commande munis de moyens d'éclairage

Abrégé

A dynamic vision sensing system, which includes a dynamic vision sensor, a AI recognition module connected to the dynamic vision sensor, and a static mode triggering module coupled to the Ai recognition module. The static mode triggering module is adapted to trigger an intensity change in an environment captured by the dynamic vision sensor to observe a static object of interest, a property that conventional dynamic vision sensor failed to capture. The motion recognition module upon detecting a change of a motion in the environment is adapted to send a command to the static mode triggering module to trigger the intensity change. An AI controlled electro-optical system is therefore proposed to capture object of interest even if the object is static by triggering effective intensity change of the static object at sensing end, hence eliminate blind spot of existing DVS system.

Classes IPC  ?

• G06V 40/20 - Mouvements ou comportement, p. ex. reconnaissance des gestes
• G06N 3/092 - Apprentissage par renforcement
• G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo

Abrégé

A method for optimizing a workflow-based neural network including an attention layer is provided. The method comprises: training the workflow-based neural network to predict a result from input elements under a prediction model with the attention layer assigning attention placements and weights, based on an original attention function, to the input elements; obtaining an original attention mask pattern and a proposed attention mask pattern; creating an attention mask updating function based on the original attention mask pattern and the proposed attention mask pattern; and combining the attention mask updating function with the original attention function to form an updated attention function.

Classes IPC  ?

• G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux

Abrégé

A method for optimizing a workflow-based neural network including an attention layer is provided. The method comprises: training the workflow-based neural network to predict a result from input elements under a prediction model with the attention layer assigning attention placements and weights, based on an original attention function, to the input elements; obtaining an original attention mask pattern and a proposed attention mask pattern; creating an attention mask updating function based on the original attention mask pattern and the proposed attention mask pattern; and combining the attention mask updating function with the original attention function to form an updated attention function.

Classes IPC  ?

• G06N 3/092 - Apprentissage par renforcement

Abrégé

An On-Off Shift Keying (OOK) receiver has non-continuous Automatic Gain Control (AGC) that sets gain at the beginning of each frame and locks the gain setting for the remainder of the frame, preventing OOK data from causing AGC loop instability. An AGC controller initializes to maximum the gain settings for a Low-Noise Amplifier (LNA), Low-Pass Filter (LPF), and a Programmable Gain Amplifier (PGA) in series that power a rectifier generating a voltage output to a 1/0 data decision circuit. A level detector compares the voltage output to two thresholds. When both thresholds are exceeded, the AGC controller steps down gain settings until the voltage output is between the two thresholds, when the gain settings are locked for the remainder of the current frame. A frame detector resets the AGC controller between frames when a long series of 0 data between frames is detected. LNA gain is reduced last.

Classes IPC  ?

• H04L 27/06 - Circuits de démodulationCircuits récepteurs
• H04B 1/16 - Circuits

Abrégé

A method and a system for road monitoring, comprises the steps of receiving, via a communication module, a first point cloud data from one or more designated road side units (RSUs) from one or more of a plurality of RSUs located in a defined geographical area; receiving, via the communication module, a second point cloud data from one or more designated vehicle on-board data processing units of vehicles located in the defined geographical area; processing, via a processing module, the first point cloud data and the second point cloud data to generate a processed point cloud data; and transmitting, via the communication module, information derived from the processed point cloud data to one or more of the RSUs and/or the vehicle on-board data processing units of vehicles located in the defined geographical area.

Classes IPC  ?

• G08G 1/01 - Détection du mouvement du trafic pour le comptage ou la commande
• H04W 4/44 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p. ex. communication véhicule-piétons pour la communication entre véhicules et infrastructures, p. ex. véhicule à nuage ou véhicule à domicile
• H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance

Abrégé

The framework predicts water-quality data from observation data associated with raw features, e.g., rainfall. In the framework, an artificial neural network (ANN) computes the predicted water-quality data from feature data associated with impact features and derived from the observation data. The impact features are learnable, and are selected from impact-feature candidates comprising directional change- (DC-based) features each indicating occurrence of DC events in a corresponding raw feature. Including the DC-based features in the candidates enhances the ANN's ability of capturing significant change patterns of water quality due to extreme/unexpected events. The ANN architecture is also configurable according to model hyperparameters, which are learnable. The impact features and model hyperparameters are learnt by differential evolution for maximizing a prediction performance achieved by the ANN, thereby enabling the ANN architecture and impact features to be automatically optimized without requiring manual adjustment by domain experts in applying the ANN to different situations.

Classes IPC  ?

• G01N 33/18 - Eau

Abrégé

The framework predicts water-quality data from observation data associated with raw features, e.g., rainfall. In the framework, an artificial neural network (ANN) computes the predicted water-quality data from feature data associated with impact features and derived from the observation data. The impact features are learnable, and are selected from impact-feature candidates comprising directional change- (DC-based) features each indicating occurrence of DC events in a corresponding raw feature. Including the DC-based features in the candidates enhances the ANN's ability of capturing significant change patterns of water quality due to extreme/unexpected events. The ANN architecture is also configurable according to model hyperparameters, which are learnable. The impact features and model hyperparameters are learnt by differential evolution for maximizing a prediction performance achieved by the ANN, thereby enabling the ANN architecture and impact features to be automatically optimized without requiring manual adjustment by domain experts in applying the ANN to different situations.

Classes IPC  ?

• G06F 30/27 - Optimisation, vérification ou simulation de l’objet conçu utilisant l’apprentissage automatique, p. ex. l’intelligence artificielle, les réseaux neuronaux, les machines à support de vecteur [MSV] ou l’apprentissage d’un modèle

Abrégé

Described is a method of synchronizing a TSN NW-TT module inside a UPF with a Grandmaster (GM) in a Time Domain of the communication network. The method comprises receiving one or more PTP or gPTP messages on an N3 interface of the UPF. The method includes determining a first time offset value between the GM and the UPF N3 interface based on information received in the PTP or gPTP messages. A timing of the UPF N3 interface is adjusted using the determined first time offset value to synchronize the time between the UPF N3 interface and the GM. The method includes determining a second time offset value between the UPF N3 interface and the NW-TT module. A timing of the NW-TT module is adjusted using the determined second time offset value to synchronize the time between the NW-TT module and the GM.

Classes IPC  ?

• H04W 56/00 - Dispositions de synchronisation

Abrégé

A system and a method for classifying and localizing surface defects with a high accuracy rate when only a small number of labeled defect data is available. The method comprises predicting a defect class for an input image using a convolutional neural network (CNN) classification model; and predicting a defect location for the input image via location ensemble with a coarse localization map and an anomaly map, which are generated using the CNN classification model and anomaly detection model respectively. The CNN classification model is built based on a CNN encoder and trained with labeled real defect images. The CNN encoder is trained by multi-task self-supervised learning with real non-defect and synthetic defect images.

Classes IPC  ?

• G06N 3/0895 - Apprentissage faiblement supervisé, p. ex. apprentissage semi-supervisé ou auto-supervisé

Abrégé

A system and a method for classifying and localizing surface defects with a high accuracy rate when only a small number of labeled defect data is available. The method comprises predicting a defect class for an input image using a convolutional neural network (CNN) classification model; and predicting a defect location for the input image via location ensemble with a coarse localization map and an anomaly map, which are generated using the CNN classification model and anomaly detection model respectively. The CNN classification model is built based on a CNN encoder and trained with labeled real defect images. The CNN encoder is trained by multi-task self-supervised learning with real non-defect and synthetic defect images.

Classes IPC  ?

• G06T 7/00 - Analyse d'image

Abrégé

A transient blockchain proxy server consolidates many individual requests to add data to a blockchain by aggregating hashed data from these requests and sending the aggregated hashed data to the blockchain network as a single request. The blockchain network adds a new block to the blockchain with the aggregated hashed data and returns a transaction identifier for the new block to the transient blockchain proxy server, which passes the transaction identifier back to all the requestors who then can directly use the blockchain network to verify the hashed data using the transaction identifier. The transient blockchain proxy server buffers all incoming requests until one of the pending requests reaches a send timepoint that is the blockchain network delay plus a buffer time before a guaranteed time of verification. All incoming requests are then consolidated and sent as a single transaction to the blockchain network. Tiered verification-time services are enabled.

Classes IPC  ?

• H04L 67/566 - Regroupement ou agrégation de demandes de service, p. ex. pour un traitement unifié

Abrégé

012nn within the extended phase rotation range.

Classes IPC  ?

• H04L 27/26 - Systèmes utilisant des codes à fréquences multiples

Abrégé

In detecting anomaly in samples, convolutional neural network (CNN) and machine-learning classifier modelled with support vectors are used. The CNN and classifier are initially trained with normal samples, and incrementally trained in retraining sessions each with self-generated anomalous samples identified in inference preceding a retraining session under consideration, thereby continually improving the anomaly-detection performance without a need to seek anomalous samples for initializing the CNN and classifier. The support vectors are selected as feature k-centers of output feature map of the CNN. Dynamic density estimation is used to determine which feature k-centers in existing support vector set are retainable in updating the support vector set in the retraining session. As such, not all feature k-centers need to be recomputed to give the support vectors in the updated support vector set. Computation effort in updating the support vector set is reduced in comparison to generating this set from scratch.

Classes IPC  ?

• G06N 3/0464 - Réseaux convolutifs [CNN, ConvNet]
• G06N 3/08 - Méthodes d'apprentissage
• G06T 7/00 - Analyse d'image

Abrégé

In detecting anomaly in samples, convolutional neural network (CNN) and machine-learning classifier modelled with support vectors are used. The CNN and classifier are initially trained with normal samples, and incrementally trained in retraining sessions each with self-generated anomalous samples identified in inference preceding a retraining session under consideration, thereby continually improving the anomaly-detection performance without a need to seek anomalous samples for initializing the CNN and classifier. The support vectors are selected as feature k-centers of output feature map of the CNN. Dynamic density estimation is used to determine which feature k-centers in existing support vector set are retainable in updating the support vector set in the retraining session. As such, not all feature k-centers need to be recomputed to give the support vectors in the updated support vector set. Computation effort in updating the support vector set is reduced in comparison to generating this set from scratch.

Classes IPC  ?

• G06T 7/00 - Analyse d'image

Abrégé

A level shifter circuit uses standard n-channel and p-channel transistors except for a pair of Lateral-Diffusion Metal-Oxide-Semiconductor (LDMOS) transistors (40, 42) that have an added lateral diffusion under the gate between the source and the conduction channel, increasing the breakdown voltage. The source of each LDMOS transistor (40, 42) connects to a drain of a transient differential transistor (70, 72) that has its gate driven by a oneshot (62, 64) that generates a pulse after an input transition. After the pulse ends a holding differential transistor (50, 52) draws a smaller bias current from the LDMOS transistors (40, 42). The source of each LDMOS transistor (40, 42) connects to the drain and gate of a p-channel sensing transistor (20, 30) that drives gates of mirror transistors (22, 24, 32, 34) generating mirrored currents to cross-coupled n-channel mirror transistors (28, 36) that drive both terminals of a bistable latch (60) that holds the output using a floating ground between driver transistors of a Buck converter switched by the bistable latch (60).

Classes IPC  ?

• H03K 19/017 - Modifications pour accélérer la commutation dans les circuits à transistor à effet de champ

Abrégé

The present invention provides a method for achieving high availability of stream control transport protocol (SCTP) connection in a microservice system. The microservice system comprises at least one access network and a core network. The access network includes at least one base station comprising at least one SCTP peer. The core network includes at least one non-SCTP-capable microservice instance acting as a SCTP service client, multiple SCTP-capable microservice instances, a service node manager and a service delegator. The method comprises: tagging each of the SCTP-capable microservice instances with a SCTP-service label; periodically scanning the microservice system, by the service node manager, to detect alive SCTP-capable microservice instances; dynamically maintaining, by the service node manager, a backend list of alive SCTP-capable microservice instances; and selecting, by the service delegator, an alive SCTP service instance from the maintained backend list according to a selection rule whenever a SCTP service request is received.

Classes IPC  ?

• H04L 67/51 - Découverte ou gestion de ceux-ci, p. ex. protocole de localisation de service [SLP] ou services du Web
• H04L 65/1101 - Protocoles de session

Abrégé

Described is a method of identifying a short-circuit (SC) like event in a circuit breaker (CB). The method comprises sampling an incoming current to the CB to determine a maximum value of a slope of a curve of the incoming current. The method includes sampling the incoming current again before a level of the incoming current reaches a predetermined, preset, selected, or calculated SC threshold value THSC for the CB. The method involves determining from the sampled incoming current that a value of the slope of the incoming current has changed from its maximum slope value to a lower slope value to thereby determine that the incoming current is indicative of a SC like event and does not comprise a real SC event.

Classes IPC  ?

• G01R 31/327 - Tests d'interrupteurs de circuit, d'interrupteurs ou de disjoncteurs
• G06F 17/00 - Équipement ou méthodes de traitement de données ou de calcul numérique, spécialement adaptés à des fonctions spécifiques

Abrégé

A method for removing stale context in a service instance, comprising: generating a user message according to UID and request instruction of received request data; routing the user message to first service instance; if target context corresponding to the user ID is saved in a global cache of a database, loading the target context from the global cache; when the loaded target context does not belong to the first service instance, setting the loaded target context to belong to the first service instance, wherein the set target context is saved into a first local cache and the global cache; and instructing to remove one or more invalid target contexts corresponding to the user ID from one or more other service instances, wherein the invalid target contexts are target contexts which do not belong to the first service instance, such that stale contexts which are the invalid target context are removed.

Classes IPC  ?

• H04L 67/63 - Ordonnancement ou organisation du service des demandes d'application, p. ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises en acheminant une demande de service en fonction du contenu ou du contexte de la demande
• H04L 67/568 - Stockage temporaire des données à un stade intermédiaire, p. ex. par mise en antémémoire
• H04L 67/5682 - Politiques ou règles de mise à jour, de suppression ou de remplacement des données stockées

Abrégé

A method for removing stale context in a service instance, comprising: generating a user message according to UID and request instruction of received request data; routing the user message to first service instance; if target context corresponding to the user ID is saved in a global cache of a database, loading the target context from the global cache; when the loaded target context does not belong to the first service instance, setting the loaded target context to belong to the first service instance, wherein the set target context is saved into a first local cache and the global cache; and instructing to remove one or more invalid target contexts corresponding to the user ID from one or more other service instances, wherein the invalid target contexts are target contexts which do not belong to the first service instance, such that stale contexts which are the invalid target context are removed.

Classes IPC  ?

• G06F 15/16 - Associations de plusieurs calculateurs numériques comportant chacun au moins une unité arithmétique, une unité programme et un registre, p. ex. pour le traitement simultané de plusieurs programmes
• H04L 67/289 - Traitement intermédiaire fonctionnellement situé à proximité de l'application consommatrice de données, p. ex. dans la même machine, dans le même domicile ou dans le même sous-réseau
• H04L 67/63 - Ordonnancement ou organisation du service des demandes d'application, p. ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises en acheminant une demande de service en fonction du contenu ou du contexte de la demande

Abrégé

Described is a method of determining a position of a mobile wireless device in a wireless communication network. The method comprises, for a plurality of clusters of transmission reception points (TRPs) associated with said mobile wireless device, measuring a parameter of first reference signals transmitted between said mobile wireless device and a single TRP from each cluster of TRPs. The method includes, based on the respective measured parameter of the first reference signals, selecting one cluster of TRPs from said plurality of clusters of TRPs. Position estimation information is determined from second reference signals transmitted between said mobile wireless device and a plurality of the TRPs comprising the selected cluster of TRPs. The determined position estimation information is used to determine a position for said mobile wireless device.

Classes IPC  ?

• H04W 64/00 - Localisation d'utilisateurs ou de terminaux pour la gestion du réseau, p. ex. gestion de la mobilité

Abrégé

A lossless data compressor prevents normalization overruns on-the-fly as symbol occurrence counts are rounded to generate symbol frequencies, allowing an encoding table generator to generate encoding table entries without waiting for the symbol frequency table to finish filling. Rounding errors are accumulated as symbols are normalized and compensated for by reducing a symbol frequency when the symbol frequency is at least 2 and the accumulated errors have exceeded a threshold. The symbol frequency is also reduced when the number of remaining states in the encoding table is insufficient for a number of remaining unprocessed symbols and states for a current encoding table entry. Since error compensation occurs as symbols are being normalized, encoding table generation is not forced to wait for all symbols in the block to be processed, reducing latency. Three pipeline stages can operate on three input blocks: symbol counting, normalization/error compensation/encoding table generation, and data encoding.

Classes IPC  ?

• H04L 27/00 - Systèmes à porteuse modulée

Abrégé

A method for charging a battery, which includes the steps of acquiring real-time information about the battery; receiving on-site input from a user, the on-site input comprising at least one of a user available time in which the battery is to be charged and a target State of Charge (SoC) to which the battery is to be charged; by using a capacity charging model of the battery, calculating a charging current for the battery based on the on-site input and the real-time information; charging the battery using the calculated charging current during a charging period to fulfill the user's energy requirement; and calibrating the capacity charging model based on information of the battery gathered during the charging period. The invention provides an adaptive battery charging method and system that decides an optimal charging current for batteries in view of on-site user commands inputted to the battery charger.

Classes IPC  ?

• H02J 7/00 - Circuits pour la charge ou la dépolarisation des batteries ou pour alimenter des charges par des batteries

Abrégé

A level shifter circuit uses standard n-channel and p-channel transistors except for a pair of Lateral-Diffusion Metal-Oxide-Semiconductor (LDMOS) transistors that have an added lateral diffusion under the gate between the source and the conduction channel, increasing the breakdown voltage. The source of each LDMOS transistor connects to a drain of a transient differential transistor that has its gate driven by a oneshot that generates a pulse after an input transition. After the pulse ends a holding differential transistor draws a smaller bias current from the LDMOS transistors. The source of each LDMOS transistor connects to the drain and gate of a p-channel sensing transistor that drives gates of mirror transistors generating mirrored currents to cross-coupled n-channel mirror transistors that drive both terminals of a bistable latch that holds the output using a floating ground between driver transistors of a Buck converter switched by the bistable latch.

Classes IPC  ?

• H03K 3/012 - Modifications du générateur pour améliorer le temps de réponse ou pour diminuer la consommation d'énergie
• H01L 29/06 - Corps semi-conducteurs caractérisés par les formes, les dimensions relatives, ou les dispositions des régions semi-conductrices
• H01L 29/10 - Corps semi-conducteurs caractérisés par les formes, les dimensions relatives, ou les dispositions des régions semi-conductrices avec des régions semi-conductrices connectées à une électrode ne transportant pas le courant à redresser, amplifier ou commuter, cette électrode faisant partie d'un dispositif à semi-conducteur qui comporte trois électrodes ou plus
• H01L 29/78 - Transistors à effet de champ l'effet de champ étant produit par une porte isolée
• H03K 3/356 - Circuits bistables

Abrégé

A lossless data compressor prevents normalization overruns on-the-fly as symbol occurrence counts are rounded to generate symbol frequencies, allowing an encoding table generator to generate encoding table entries without waiting for the symbol frequency table to finish filling. Rounding errors are accumulated as symbols are normalized and compensated for by reducing a symbol frequency when the symbol frequency is at least 2 and the accumulated errors have exceeded a threshold. The symbol frequency is also reduced when the number of remaining states in the encoding table is insufficient for a number of remaining unprocessed symbols and states for a current encoding table entry. Since error compensation occurs as symbols are being normalized, encoding table generation is not forced to wait for all symbols in the block to be processed, reducing latency. Three pipeline stages can operate on three input blocks: symbol counting, normalization/error compensation/encoding table generation, and data encoding.

Classes IPC  ?

• H03M 13/00 - Codage, décodage ou conversion de code pour détecter ou corriger des erreursHypothèses de base sur la théorie du codageLimites de codageMéthodes d'évaluation de la probabilité d'erreurModèles de canauxSimulation ou test des codes
• H03M 7/30 - CompressionExpansionÉlimination de données inutiles, p. ex. réduction de redondance
• H03M 7/40 - Conversion en, ou à partir de codes de longueur variable, p. ex. code Shannon-Fano, code Huffman, code Morse

Abrégé

An On-Off Shift Keying (OOK) receiver has non-continuous Automatic Gain Control (AGC) that sets gain at the beginning of each frame and locks the gain setting for the remainder of the frame, preventing OOK data from causing AGC loop instability. An AGC controller initializes to maximum the gain settings for a Low-Noise Amplifier (LNA), Low-Pass Filter (LPF), and a Programmable Gain Amplifier (PGA) in series that power a rectifier generating a voltage output to a 1/0 data decision circuit. A level detector compares the voltage output to two thresholds. When both thresholds are exceeded, the AGC controller steps down gain settings until the voltage output is between the two thresholds, when the gain settings are locked for the remainder of the current frame. A frame detector resets the AGC controller between frames when a long series of 0 data between frames is detected. LNA gain is reduced last.

Classes IPC  ?

• H04B 1/04 - Circuits
• H04B 1/7176 - Affectation des données, p. ex. modulation

Abrégé

A method and system (100) for detecting short-term stress of a subject person and generating alerts in an indoor environment are disclosed. The system may receive data on the subject person's heart rate, galvanic skin response, and accelerometer movement from a wearable device, and also capture image frames through a camera. After that, the system may perform bio-signal analysis in accordance with the heart rate and the galvanic skin response data, and perform skeletal motion analysis in accordance with the image frames. Based on bio-signal index and skin conductance index generated from the bio-signal analysis and skeletal motion analysis respectively, the system may perform data fusion to determine the short-term stress.

Classes IPC  ?

• A61B 5/16 - Dispositifs pour la psychotechnieTest des temps de réaction
• A61B 5/0531 - Mesure de l’impédance de la peau
• A61B 5/11 - Mesure du mouvement du corps entier ou de parties de celui-ci, p. ex. tremblement de la tête ou des mains ou mobilité d'un membre

Abrégé

A train-linking lossless data compressor examines a block of data and uses a same coder to generate a same code when all data values in the input block are identical. When the input data is not all the same value, then a Gaussian coder, a Laplace coder, and a delta coder are activated in parallel. The three compressed code lengths are compared and the smallest code length is output as the compressed code when it is smaller than a copy code length. The copy code is a tag followed by copying all the data in the input block. When the smallest of the three compressed code lengths is larger than the copy code length, the file is not compressible, and the copy code is output. No frequency table is required so latency is low. The delta coder subtracts data values from an average value of the last data block.

Classes IPC  ?

• H04N 19/52 - Traitement de vecteurs de mouvement par encodage par encodage prédictif
• G06N 3/042 - Réseaux neuronaux fondés sur la connaissanceReprésentations logiques de réseaux neuronaux

Abrégé

Systems and methods which provide time of flight (ToF) measurement techniques implementing threshold-based sampling for waveform digitizing to generate a signal waveform representing a detected ToF measurement signal from which a ToF distance measurement is determinable are described. An example ToF measurement system may apply one or more curve fitting techniques, such as using one or more curve fitting hardware accelerators, to data from threshold-based sampling for waveform digitizing of the received pulse. Examples of a ToF measurement system may implement time-to-digital converters (TDCs) to sample a received pulse using a plurality of thresholds. ToF measurement systems of examples may implement multi-point filtering, such as using a hardware accelerator.

Classes IPC  ?

• G01S 7/487 - Extraction des signaux d'écho désirés
• G01S 17/08 - Systèmes déterminant les données relatives à la position d'une cible pour mesurer la distance uniquement
• G01S 17/10 - Systèmes déterminant les données relatives à la position d'une cible pour mesurer la distance uniquement utilisant la transmission d'ondes à modulation d'impulsion interrompues

Abrégé

A transient blockchain proxy server consolidates many individual requests to add data to a blockchain by aggregating hashed data from these requests and sending the aggregated hashed data to the blockchain network as a single request. The blockchain network adds a new block to the blockchain with the aggregated hashed data and returns a transaction identifier for the new block to the transient blockchain proxy server, which passes the transaction identifier back to all the requestors who then can directly use the blockchain network to verify the hashed data using the transaction identifier. The transient blockchain proxy server buffers all incoming requests until one of the pending requests reaches a send timepoint that is the blockchain network delay plus a buffer time before a guaranteed time of verification. All incoming requests are then consolidated and sent as a single transaction to the blockchain network. Tiered verification-time services are enabled.

Classes IPC  ?

• H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
• H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
• H04L 9/08 - Répartition de clés

Abrégé

A method and system for detecting short-term stress of a subject person and generating alerts in an indoor environment are disclosed. The system may receive data on the subject person's heart rate, galvanic skin response, and accelerometer movement from a wearable device, and also capture image frames through a camera. After that, the system may perform bio-signal analysis in accordance with the heart rate and the galvanic skin response data, and perform skeletal motion analysis in accordance with the image frames. Based on bio-signal index and skin conductance index generated from the bin-signal analysis and skeletal motion analysis respectively, the system may perform data fusion to determine the short-term stress.

Classes IPC  ?

• A61B 5/16 - Dispositifs pour la psychotechnieTest des temps de réaction
• A61B 5/024 - Mesure du pouls ou des pulsations cardiaques
• A61B 5/0533 - Mesure de la réaction cutanée galvanique
• A61B 5/11 - Mesure du mouvement du corps entier ou de parties de celui-ci, p. ex. tremblement de la tête ou des mains ou mobilité d'un membre
• G06V 10/80 - Fusion, c.-à-d. combinaison des données de diverses sources au niveau du capteur, du prétraitement, de l’extraction des caractéristiques ou de la classification
• G06V 20/40 - ScènesÉléments spécifiques à la scène dans le contenu vidéo
• G06V 40/20 - Mouvements ou comportement, p. ex. reconnaissance des gestes

Abrégé

A data-compression analyzer can rapidly make a binary decision to compress or not compress an input data block or can use a slower neural network to predict the block's compression ratio with a regression model. A Concentration Value (CV) that is the sum of the squares of the frequencies and a Number of Zero (NZ) symbols are calculated from an un-sorted symbol frequency table. A rapid decision to compress is signaled when their product CV*NZ exceeds a horizontal threshold THH. During training, CV*NZ is plotted as a function of compression ratio C % for many training data blocks. Different test values of THH are applied to the plot to determine true and false positive rates that are plotted as a Receiver Operating Characteristic (ROC) curve. The point on the ROC curve having the largest Youden index is selected as the optimum THH for use in future binary decisions.

Classes IPC  ?

• H03M 7/30 - CompressionExpansionÉlimination de données inutiles, p. ex. réduction de redondance

Abrégé

A data-compression analyzer can rapidly make a binary decision to compress or not compress an input data block or can use a slower neural network to predict the block's compression ratio with a regression model. A Concentration Value (CV) that is the sum of the squares of the frequencies and a Number of Zero (NZ) symbols are calculated from an un-sorted symbol frequency table. A rapid decision to compress is signaled when their product CV*NZ exceeds a horizontal threshold THH. During training, CV*NZ is plotted as a function of compression ratio C%for many training data blocks. Different test values of THH are applied to the plot to determine true and false positive rates that are plotted as a Receiver Operating Characteristic (ROC) curve. The point on the ROC curve having the largest Youden index is selected as the optimum THH for use in future binary decisions.

Classes IPC  ?

• G06N 3/0495 - Réseaux quantifiésRéseaux parcimonieuxRéseaux compressés

Abrégé

A line-scanning three-dimensional sensing system measures a surface profile of an object. In the system, a dispersion optical module (DOM) performs a forward optical process of chromatically dispersing a polychromatic linear light beam into constituent narrowband linear light beams (CNLLBs) and focusing the CNLLBs on different focal planes to form a rainbow light pattern for illuminating a scanned surface of the object. The illuminated object displays an information-bearing color image (IBCI) containing height information of the scanned surface. The DOM captures the IBCI, and performs a backward optical process of optically condensing the captured IBCI to form an elongated light pattern. The backward optical process is an inverse of the forward one. A slit spatially filters the elongated light pattern to form an output light line. A height profile of the scanned surface is obtained by analyzing a spectral content at each point of the output light line.

Classes IPC  ?

• G01B 11/25 - Dispositions pour la mesure caractérisées par l'utilisation de techniques optiques pour mesurer des contours ou des courbes en projetant un motif, p. ex. des franges de moiré, sur l'objet
• G02B 27/09 - Mise en forme du faisceau, p. ex. changement de la section transversale, non prévue ailleurs

Abrégé

A line-scanning three-dimensional sensing system measures a surface profile of an object. In the system, a dispersion optical module (DOM) (110) performs a forward optical process of chromatically dispersing a polychromatic linear light beam (131) into constituent narrowband linear light beams (CNLLBs) (180) and focusing the CNLLBs (180) on different focal planes (183a-c) to form a rainbow light pattern (181) for illuminating a scanned surface (283) of the object (95). The illuminated object (95) displays an information-bearing color image (IBCI) (282) containing height information of the scanned surface (283). The DOM (110) captures the IBCI (282), and performs a backward optical process of optically condensing the captured IBCI (282) to form an elongated light pattern (210). The backward optical process is an inverse of the forward one. A slit (122) spatially filters the elongated light pattern (210) to form an output light line (220). A height profile of the scanned surface is obtained by analyzing a spectral content at each point of the output light line (220).

Classes IPC  ?

• G01B 11/25 - Dispositions pour la mesure caractérisées par l'utilisation de techniques optiques pour mesurer des contours ou des courbes en projetant un motif, p. ex. des franges de moiré, sur l'objet

Abrégé

A movable camera travels along an inspection path for optically inspecting an inspection surface of an object for defect detection. In planning the inspection path, a set of viewpoints on the inspection surface is generated. Each viewpoint is associated with a patch, which is a largest area of the inspection surface within a field of view (FOV) of the camera when the camera is located over the viewpoint for capturing an image of FOV. An effective region of the patch is advantageously predicted by a neural network according to a three-dimensional geometric characterization of the patch such that the predicted effective region is valid for defect detection based on the captured image. A valid area is one whose corresponding area on the captured image is not blurred and is neither underexposed nor overexposed. The inspection path is determined according to respective effective regions associated with the set of viewpoints.

Classes IPC  ?

• G06F 30/15 - Conception de véhicules, d’aéronefs ou d’embarcations

Abrégé

A movable camera travels along an inspection path for optically inspecting an inspection surface of an object for defect detection. In planning the inspection path, a set of viewpoints on the inspection surface is generated. Each viewpoint is associated with a patch, which is a largest area of the inspection surface within a field of view (FOV) of the camera when the camera is located over the viewpoint for capturing an image of FOV. An effective region of the patch is advantageously predicted by a neural network according to a three-dimensional geometric characterization of the patch such that the predicted effective region is valid for defect detection based on the captured image. A valid area is one whose corresponding area on the captured image is not blurred and is neither underexposed nor overexposed. The inspection path is determined according to respective effective regions associated with the set of viewpoints.

Classes IPC  ?

• H04N 23/695 - Commande de la direction de la caméra pour modifier le champ de vision, p. ex. par un panoramique, une inclinaison ou en fonction du suivi des objets
• G01N 21/88 - Recherche de la présence de criques, de défauts ou de souillures
• G01N 21/95 - Recherche de la présence de criques, de défauts ou de souillures caractérisée par le matériau ou la forme de l'objet à analyser
• G06T 7/73 - Détermination de la position ou de l'orientation des objets ou des caméras utilisant des procédés basés sur les caractéristiques

Abrégé

A multidimensional knowledge transfer model for predicting CTR of a computational ad, the multidimensional knowledge transfer model comprises: a pre-processor for building an ad group node graph based on similarities among ad group nodes, an ad campaign node graph from merging the ad group node graph, and an ad account node graph from merging the ad campaign node graph. The multidimensional knowledge transfer model further comprises a multi-knowledge CTR prediction model for each of the ad account, ad campaign, and ad group layers. The multi-knowledge CTR prediction model predicts the respective node's CTR from the ad account node graph, ad campaign node graph, or ad group node graph, features of the audience group, and features of the node having its CTR predicted appended with the hidden vector of its parent node extracted from the upper layer multi-knowledge CTR prediction model.

Classes IPC  ?

• G06Q 30/0272 - Période d’exposition à la publicité

Abrégé

A multidimensional knowledge transfer model for predicting CTR of a computational ad, the multidimensional knowledge transfer model comprises: a pre-processor for building an ad group node graph based on similarities among ad group nodes, an ad campaign node graph from merging the ad group node graph, and an ad account node graph from merging the ad campaign node graph. The multidimensional knowledge transfer model further comprises a multi-knowledge CTR prediction model for each of the ad account, ad campaign, and ad group layers. The multi-knowledge CTR prediction model predicts the respective node's CTR from the ad account node graph, ad campaign node graph, or ad group node graph, features of the audience group, and features of the node having its CTR predicted appended with the hidden vector of its parent node extracted from the upper layer multi-knowledge CTR prediction model.

Classes IPC  ?

• G06Q 30/02 - MarketingEstimation ou détermination des prixCollecte de fonds

Abrégé

A level-shifting output buffer has cascode transistors with varying rather than fixed gate bias voltages. An adaptive regulator bypasses the I/O pad voltage to a regulator output when the I/O begins switching, but later clamps the regulator output to a middle bias voltage. The regulator output can be applied to a supply terminal ofa buffer that drives the gate ofthe cascode transistor. Since the adaptive regulator follows the I/O pad voltage as switching begins, avoltage boost is provided to the gates ofthe cascode transistors, allowing for higher currents or smaller cascode transistors and preventing over-voltage stress. The adaptive regulator has an n-channel bypass transistor between the I/O pad and the regulator output, and an n-channel clamp transistor between the regulator output and the middle bias, with a gate driven from the I/O pad by either a p-channel gate-biasing transistor or an n-channel gate-biasing transistor.

Classes IPC  ?

• H03K 19/0185 - Dispositions pour le couplageDispositions pour l'interface utilisant uniquement des transistors à effet de champ

Abrégé

Described is a method of controlling movement of a mobile robot (10) in the event of a localization failure. The method comprises, on an occurrence of the localization failure, receiving an image from an image sensor of the mobile robot (10). The method includes splitting received image into at least two vertical portions and determining if one of said at least two vertical portions is indicative of a passable path. The method includes controlling the mobile robot (10) to travel along the passable path indicated by a selected one of said at least two vertical portions.

Classes IPC  ?

• G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions

Abrégé

A two-stage power converter has a Power-Factor Converter (PFC) and a Dual Active Bridge (DAB) converter connected together by a DC link voltage. The DAB converter outputs a battery voltage with a battery current. A PFC controller divides a reference power constant by the battery voltage to get a battery current reference that is multiplied by a constant and compared to the DC link voltage to adjust Pulse-Width-Modulation (PWM) control signals to the PFC. The reference power constant is compared to the battery current during Constant-Power mode to cause a DAB controller to modulate duty ratio and phase difference between primary and secondary-side PWM control signals to the DAB converter. The DAB converter duty ratio and phase difference are modulated by comparing the battery current to a battery current limit during Constant-Current mode and by comparing the battery voltage to a battery voltage limit during Constant-Voltage mode.

Classes IPC  ?

• H02M 3/335 - Transformation d'une puissance d'entrée en courant continu en une puissance de sortie en courant continu avec transformation intermédiaire en courant alternatif par convertisseurs statiques utilisant des tubes à décharge avec électrode de commande ou des dispositifs à semi-conducteurs avec électrodes de commande pour produire le courant alternatif intermédiaire utilisant des dispositifs du type triode ou transistor exigeant l'application continue d'un signal de commande utilisant uniquement des dispositifs à semi-conducteurs
• H02J 7/06 - Régulation du courant ou de la tension de charge utilisant des tubes à décharge ou des dispositifs à semi-conducteurs

Abrégé

A method for detecting and tracking target object in a captured video using convolutional neural network (CNN) is provided. The method includes: inputting image data into a detecting model to generate detection results, wherein the detecting model is constructed by the CNN; inputting the image data into tracking models to generate tracking results; performing detection score enhancement operation according to the detection results and the tracking results to obtain enhanced detection results; matching the enhanced detection results and the tracking results by a matching operation; processing matched results and unmatched target detection results and unmatched target tracking results; and selectively updating the tracking models using tracking reliability estimation according to the matched results.

Classes IPC  ?

• G06T 7/73 - Détermination de la position ou de l'orientation des objets ou des caméras utilisant des procédés basés sur les caractéristiques

Abrégé

A method for detecting and tracking target object in a captured video using convolutional neural network (CNN) is provided. The method includes: inputting image data into a detecting model to generate detection results, wherein the detecting model is constructed by the CNN; inputting the image data into tracking models to generate tracking results; performing detection score enhancement operation according to the detection results and the tracking results to obtain enhanced detection results; matching the enhanced detection results and the tracking results by a matching operation; processing matched results and unmatched target detection results and unmatched target tracking results; and selectively updating the tracking models using tracking reliability estimation according to the matched results.

Classes IPC  ?

• G06T 7/70 - Détermination de la position ou de l'orientation des objets ou des caméras
• G06T 7/20 - Analyse du mouvement

Abrégé

Systems and methods which provide single nanostructure-integrated metalens configurations implementing light focusing functionality are described. A single nanostructure-integrated metalens may comprise an optical substrate having a preconfigured mapping of integrated nanostructures providing metasurfaces for modulating the behaviors of electromagnetic waves to implement a thin, flat lens. A period distance for the nanostructures, a height of the nanostructures, and a quantization for lateral sizes of the nanostructures may be selected for a particular single nanostructure-integrated metalens configuration. One or more phase maps configured for light focusing may be computed with respect to one or more design wavelengths selected for focusing. The consolidated phase retardation requirements of the one ore more phase maps may be satisfied by a preconfigured mapping which defines the phase distribution for the nanostructures of a single nanostructure-integrated metalens implementation.

Classes IPC  ?

• G02B 1/00 - Éléments optiques caractérisés par la substance dont ils sont faitsRevêtements optiques pour éléments optiques
• G02B 3/02 - Lentilles simples ou composées à surfaces non sphériques

Abrégé

Systems and methods which provide single nanostructure-integrated metalens (110) configurations implementing projector and light shaper functionality are described. A single nanostructure-integrated metalens (110) may comprise an optical substrate (111) having a preconfigured mapping of integrated nanostructures (112) providing metasurfaces for modulating the behaviors of electromagnetic waves to implement a thin, flat lens. A period distance (P) for the nanostructures (112), a height (H) of the nanostructures (112), and a quantization for lateral sizes (S) of the nanostructures (112) may be selected for a particular single nanostructure-integrated metalens (110) configuration. A first phase map may be computed with respect to structured light generation and a second phase map may be computed with respect to light collimation, wherein fusion of these phase maps may be used to define a preconfigured mapping for the nanostructures (112) of a single nanostructure-integrated metalens (110) implementation. The phase distribution of the first phase map may be inverse designed, such as using an inverse phase design technique.

Classes IPC  ?

• G02B 3/02 - Lentilles simples ou composées à surfaces non sphériques
• G02B 7/02 - Montures, moyens de réglage ou raccords étanches à la lumière pour éléments optiques pour lentilles
• G03B 21/14 - Projecteurs ou visionneuses du type par projectionLeurs accessoires Détails
• G02B 27/00 - Systèmes ou appareils optiques non prévus dans aucun des groupes ,

Abrégé

A power-converter module has a switching Printed Circuit Board (PCB) with power transistors generating heat. Ground, an input power supply, and an output power supply to the power transistors connect through metal traces on the switching PCB directly to interposer heat sinks that are soldered to the switching PCB. Copper bars attached to the bottoms of interposer heat sinks fit in holes in a system PCB to make connections. The metal traces and interposer heat sinks carry supply or ground currents and heat away from the power transistors. These power and ground currents continue from the interposer heat sinks through the copper bars to the system PCB. An interposer PCB has soler pads and solder balls to carry control signals from the system PCB to the switching PCB, bypassing the interposer heat sinks. Copper bars can be sintered, soldered, or welded to or integral with the interposer heat sinks.

Classes IPC  ?

• H05K 7/20 - Modifications en vue de faciliter la réfrigération, l'aération ou le chauffage
• H01R 12/52 - Connexions fixes pour circuits imprimés rigides ou structures similaires se raccordant à d'autres circuits imprimés rigides ou à des structures similaires

Abrégé

A method for analyzing environmental sounds to identify repeating noises due to power equipment for purposes of controlling noise pollution is disclosed. Ambient sounds are sampled with microphones and the resulting data analyzed by an edge computing device. The samples are compared to stored data with a convolutional neural network by the edge computing device which also performs pitch shifting and cycle shifting to reduce false negatives. Positive results are reported via LoRa and/or 4G to a cloud platform and/or backend server.

Classes IPC  ?

• H04R 29/00 - Dispositifs de contrôleDispositifs de tests
• G06N 3/08 - Méthodes d'apprentissage
• H04R 3/00 - Circuits pour transducteurs
• G10K 11/16 - Procédés ou dispositifs de protection contre le bruit ou les autres ondes acoustiques ou pour amortir ceux-ci, en général

Abrégé

A multi-functional, computer-aided gastroscopy system (100) optimized with integrated AI solutions is disclosed. The system (100) makes use of multiple deep-learning neural models (106) to achieve low latency and high-performance requirements for multiple tasks. The optimization is made at three levels: architectural, modular and functional level. At architectural level, the models (106) are designed in such a way that it is able to accomplish HP infection classification and detection of some lesions for one inference in order to reduce computation costs. At modular level, as a sub-model of HP infection classification, the site recognition model (207) is optimized with temporal information. It not only improves the performance of HP infection classification, but also plays important roles for lesion detection and procedure status determination. At functional level, the inference latency is minimized by configuration and resource aware optimization. Also at functional level, the preprocessing is speeded up by image resizing parallelization and unified preprocessing.

Classes IPC  ?

• G16H 40/60 - TIC spécialement adaptées à la gestion ou à l’administration de ressources ou d’établissements de santéTIC spécialement adaptées à la gestion ou au fonctionnement d’équipement ou de dispositifs médicaux pour le fonctionnement d’équipement ou de dispositifs médicaux
• G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
• G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
• G06N 3/02 - Réseaux neuronaux
• A61B 1/273 - Instruments pour procéder à l'examen médical de l'intérieur des cavités ou des conduits du corps par inspection visuelle ou photographique, p. ex. endoscopesDispositions pour l'éclairage dans ces instruments pour l'appareil digestif supérieur, p. ex. œsophagoscopes, gastroscopes

Abrégé

A multi-functional, computer-aided gastroscopy system optimized with integrated AI solutions is disclosed. The system makes use of multiple deep-learning neural models to achieve low latency and high-performance requirements for multiple tasks. The optimization is made at three levels: architectural, modular and functional level. At architectural level, the models are designed in such a way that it is able to accomplish HP infection classification and detection of some lesions for one inference in order to reduce computation costs. At modular level, as a sub-model of HP infection classification, the site recognition model is optimized with temporal information. It not only improves the performance of HP infection classification, but also plays important roles for lesion detection and procedure status determination. At functional level, the inference latency is minimized by configuration and resource aware optimization. Also at functional level, the preprocessing is speeded up by image resizing parallelization and unified preprocessing.

Classes IPC  ?

• G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
• A61B 1/00 - Instruments pour procéder à l'examen médical de l'intérieur des cavités ou des conduits du corps par inspection visuelle ou photographique, p. ex. endoscopesDispositions pour l'éclairage dans ces instruments
• A61B 1/273 - Instruments pour procéder à l'examen médical de l'intérieur des cavités ou des conduits du corps par inspection visuelle ou photographique, p. ex. endoscopesDispositions pour l'éclairage dans ces instruments pour l'appareil digestif supérieur, p. ex. œsophagoscopes, gastroscopes
• G06T 1/20 - Architectures de processeursConfiguration de processeurs p. ex. configuration en pipeline
• G06T 7/00 - Analyse d'image
• G06V 10/40 - Extraction de caractéristiques d’images ou de vidéos

Abrégé

A voltage detector has a diode ladder with one or more diodes connected in series between a battery voltage input and an upper measuring node. A measuring diode is connected between the upper measuring node and a lower measuring node. A resistor and a power-down switch are connected in series between the lower measuring node and a ground. An analog input to an Analog-to-Digital Converter (ADC) is connected by a switch to the upper measuring node to generate an upper digital value. Then the switch connects the analog input to the lower measuring node to generate a lower digital value. The difference between the upper and lower digital values is the diode voltage drop across the measuring diode and is multiplied by a number of diodes in the diode ladder and added to the upper digital value to generate a battery voltage measurement.

Classes IPC  ?

• H02H 9/02 - Circuits de protection de sécurité pour limiter l'excès de courant ou de tension sans déconnexion sensibles à un excès de courant
• G01R 19/25 - Dispositions pour procéder aux mesures de courant ou de tension ou pour en indiquer l'existence ou le signe utilisant une méthode de mesure numérique

Abrégé

A visual content search and retrieval platform comprising an object detection model, a coarse-grained image classification model, and a selection of fine-grained image classification models. During inference, the object detection model locates and extracts a query object in a query image; the coarse-grained image classification model classifies the query object's meta-category; the fine-grained image classification model trained and optimized for the meta-category of the query object is selected; and the selected fine-grained image classification model searches and retrieves from an image database images of objects most similar to the query object. The fine-grained image classification model is implemented by a multi-focus fine-grained image search and retrieval apparatus comprising a class learning module learned to generate the query object's overall appearance query features; a local description module learned to generate the query object's local details query features; an outline description module learned to generate the query object's outline query features.

Classes IPC  ?

• G06F 16/583 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des métadonnées provenant automatiquement du contenu

Abrégé

An integrated MOSFET-JFET device made from a Silicon-Carbide (SiC) wafer has N+ source, P body diode, and upper N regions that form vertical MOSFETs on the sidewalls of polysilicon gates. An N substrate under the upper N region forms a drift region that is pinched by the JFET to limit saturation current. Trenches are formed between MOSFETs. JFETs are formed by doping the bottom and sidewalls of the trenches to form P+ taps to the N substrate. P islands within the N substrate are formed underneath the P+ taps. These P islands are wider near the surface but are successively narrower with increased vertical spacing deeper into the N substrate. This P-island tapering provides a tapered shape to the JFET depletion region that pinches the MOSFET drift region in the N substrate to limit saturation current and yet reduce linear-region ON resistance.

Classes IPC  ?

• H10D 30/60 - Transistors à effet de champ à grille isolée [IGFET]
• H10D 62/17 - Régions semi-conductrices connectées à des électrodes ne transportant pas de courant à redresser, amplifier ou commuter, p. ex. régions de canal
• H10D 62/832 - Corps semi-conducteurs, ou régions de ceux-ci, de dispositifs ayant des barrières de potentiel caractérisés par les matériaux étant des matériaux du groupe IV, p. ex. Si dopé B ou Ge non dopé étant des matériaux du groupe IV comprenant deux éléments ou plus, p. ex. SiGe

Abrégé

A visual content search and retrieval platform comprising an object detection model, a coarse-grained image classification model, and a selection of fine-grained image classification models. During inference, the object detection model locates and extracts a query object in a query image; the coarse-grained image classification model classifies the query object's meta-category; the fine-grained image classification model trained and optimized for the meta-category of the query object is selected; and the selected fine-grained image classification model searches and retrieves from an image database images of objects most similar to the query object. The fine-grained image classification model is implemented by a multi-focus fine-grained image search and retrieval apparatus comprising a class learning module learned to generate the query object's overall appearance query features; a local description module learned to generate the query object's local details query features; an outline description module learned to generate the query object's outline query features.

Classes IPC  ?

• G06F 16/532 - Formulation de requêtes, p. ex. de requêtes graphiques
• G06F 16/538 - Présentation des résultats des requêtes
• G06F 16/55 - GroupementClassement
• G06N 3/045 - Combinaisons de réseaux
• G06N 3/0464 - Réseaux convolutifs [CNN, ConvNet]