09 - Appareils et instruments scientifiques et électriques
Produits et services
Downloadable and recorded computer software for research,
modeling, data collection, data ingestion, data storage, and
simulations in the fields of biology, synthetic biology,
pharmaceutical preparations, biotechnology, living systems,
renewable materials, chemicals, organisms, and bioprocesses.
2.
DETECTING SURREPTITIOUS SPEECH USING MACHINE LEARNING MODELS
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for detecting surreptitious speech. One of the methods includes obtaining data representing a sequence of text; obtaining a sequence of tokens for the sequence of text comprising one or more groups of tokens, wherein each group comprises two or more tokens; processing the one or more groups of tokens using a first machine learning model to identify tokens that are out of context in the sequence of tokens; and providing data representing the identified tokens.
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable AI software for assisting in real estate
development, building construction, and architectural
design, generating pre-development building designs,
securing permitting and capital allocation for real estate
projects, real estate marketing, identifying building
locations and nature of real estate projects, and providing
operative construction drawings; downloadable AI software
for analyzing and compiling real estate, construction, and
architectural data, generating and enhancing models, and
generating text, images, audiovisual material, and document
in response to prompts; downloadable software utilizing
artificial intelligence for use in providing information and
predictive recommendations on real estate development,
building construction, and architectural design;
downloadable computer chatbot software for simulating
conversations; downloadable computer chatbot software for
assisting in real estate development, building construction,
and architectural design, generating pre-development
building designs, securing permitting and capital allocation
for real estate projects, real estate marketing, identifying
building locations and nature of real estate projects, and
providing operative construction drawings. Business advisory and information services in the fields of
architecture, real estate, interior design and urban
planning design; providing business planning and marketing
solutions for real estate professionals; real estate
marketing analysis; real estate sales management; business
research and data analysis services in the field of in the
fields of architecture, interior design and urban planning
design; business consulting services in the fields of
architecture, real estate, interior design and urban
planning design; data processing services in the fields of
architecture, real estate, interior design and urban
planning design; analyzing and compiling business data in
the fields of architecture, real estate, interior design and
urban planning design; compiling and analyzing statistics,
data and other sources of information for business purposes
in the fields of architecture, real estate, interior design
and urban planning design. Providing online non-downloadable software for assisting in
real estate development, building construction, and
architectural design, generating pre-development building
designs, securing permitting and capital allocation for real
estate projects, real estate marketing, identifying building
locations and nature of real estate projects, and providing
operative construction drawings; Software as a Service
(SaaS) services featuring software for assisting in real
estate development, building construction, and architectural
design, generating pre-development building designs,
securing permitting and capital allocation for real estate
projects, real estate marketing, identifying building
locations and nature of real estate projects, and providing
operative construction drawings; providing online
non-downloadable AI software for analyzing and compiling
real estate, construction, and architectural data,
generating and enhancing models, and generating text,
images, audiovisual material, and document in response to
prompts; Software as a Service (SaaS) services featuring AI
software for analyzing and compiling real estate,
construction, and architectural data, generating and
enhancing models, and generating text, images, audiovisual
material, and document in response to prompts; providing
online non-downloadable software utilizing artificial
intelligence for use in providing information and predictive
recommendations on real estate development, building
construction, and architectural design; Software as a
Service (SaaS) services featuring software utilizing
artificial intelligence for use in providing information and
predictive recommendations on real estate development,
building construction, and architectural design; providing
online non-downloadable computer chatbot software for
simulating conversations; providing online non-downloadable
computer chatbot software for assisting in real estate
development, building construction, and architectural
design, generating pre-development building designs,
securing permitting and capital allocation for real estate
projects, real estate marketing, identifying building
locations and nature of real estate projects, and providing
operative construction drawings; architectural services;
residential and commercial building design.
Techniques for generating a subsurface image include analyzing a region to be sensed to determine a plurality of reflector locations; and performing a survey. Performing the survey includes irradiating a plurality of reflectors positioned in the plurality of determined reflector locations with coherent electromagnetic energy; identifying one or more vibrations of the plurality of reflectors based on reflected electromagnetic energy from the plurality of reflectors; and generating survey data associated with the identified vibrations for at least one reflector of the plurality of reflectors. The techniques include providing the survey data as input to a machine learning algorithm; and generating, using the machine learning algorithm, a subsurface image associated with the region to be sensed.
G01H 9/00 - Mesure des vibrations mécaniques ou des ondes ultrasonores, sonores ou infrasonores en utilisant des moyens sensibles aux radiations, p. ex. des moyens optiques
G01V 1/00 - SéismologieProspection ou détection sismique ou acoustique
G01V 1/22 - Transmission des signaux sismiques aux appareils d'enregistrement ou de traitement
G01V 1/28 - Traitement des données sismiques, p. ex. pour l’interprétation ou pour la détection d’événements
6.
PERFORMING FACT CHECKING USING MACHINE LEARNING MODELS
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing tasks. One of the methods includes receiving a trigger from a user; responsive to the trigger, obtaining text data representing one or more subwords to be processed; obtaining data representing a plurality of clusters, wherein each cluster comprises one or more documents of a plurality of documents; processing the text data to identify one or more clusters of the plurality of clusters that are relevant to the text data; for each of the one or more identified clusters: identifying one or more documents of the identified cluster that are relevant to the text data; identifying one or more documents that contradict the text data of the one or more identified documents that are relevant to the text data; and providing data representing the one or more identified documents that contradict the text data.
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for detecting surreptitious speech. One of the methods includes obtaining data representing a sequence of text; obtaining a sequence of tokens for the sequence of text comprising one or more groups of tokens, wherein each group comprises two or more tokens; processing the one or more groups of tokens using a first machine learning model to identify tokens that are out of context in the sequence of tokens; and providing data representing the identified tokens.
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing tasks. One of the methods includes receiving a trigger from a user; responsive to the trigger, obtaining text data representing one or more subwords to be processed; obtaining data representing a plurality of clusters, wherein each cluster comprises one or more documents of a plurality of documents; processing the text data to identify one or more clusters of the plurality of clusters that are relevant to the text data; for each of the one or more identified clusters: identifying one or more documents of the identified cluster that are relevant to the text data; identifying one or more documents that contradict the text data of the one or more identified documents that are relevant to the text data; and providing data representing the one or more identified documents that contradict the text data.
Methods, systems, and apparatus for receiving an image file recording an image and a set of metadata, determining a search space based on one or more of at least a portion of the set of metadata and auxiliary data, generating a set of candidate images based on the search space, identifying a candidate image in the set of candidate images as a best matching image relative to the image, the candidate image being associated with a set of candidate metadata, providing a set of augmented metadata for the image based on the set of metadata and the set of candidate metadata, the set of augmented metadata including at least a portion of the set of candidate metadata, and outputting a geographic features file that is generated using the set of augmented metadata, the geographic features file including data representing one or more geographic features represented in the image file.
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable software for use in connection with utilities, namely, for providing information and analyzing data on energy usage, renewable energy, energy savings, energy distribution, energy transmission, energy measurement, inter-connection of energy assets, utilities assets, utilities repairs, route optimization, data optimization, customer service, energy finance, and energy forecasting; Downloadable software utilizing artificial intelligence and machine learning for use in connection with utilities services and assets, namely, for providing customers with access to utility account data and for providing information, contextual prediction, personalization, predictive analytics, and analyzing data and metrics on energy usage, inter-connection of energy assets, renewable energy, energy savings, energy distribution, energy transmission, energy measurement, utilities assets, utilities repairs, route optimization, data optimization, customer service, energy finance, and energy forecasting; Downloadable software for computing energy usage, savings, distribution, transmission, measurement, and forecasting; Downloadable simulation software for modeling, planning, designing, operating, and optimizing utilities services, utilities assets, energy grids, energy inter-connections, renewable energy grids, energy distribution, energy transmission, energy measurements, and also for energy forecasting; Downloadable application programming interface (API) software; Downloadable software development kits (SDK) Consulting services in the fields of electrical grids, energy usage, renewable energy, inter-connection of energy assets, energy usage management, and energy savings; business consulting services in the field of energy measurement to improve energy efficiency within residential, commercial, industrial and institutional facilities; Energy usage management; providing information in the fields of energy usage management, electrical grids, inter-connection of energy assets, energy savings in the nature of energy efficiency, and energy measurement Research, design and development of computer hardware and software; Computer services, namely, operating computer systems and computer networks featuring energy transmission, distribution, and management software for public utilities and others for energy usage, renewable energy, energy savings, energy distribution, energy transmission, energy measurement, inter-connection of energy assets, utilities assets, utilities repairs, route optimization, data optimization, customer service, energy finance, and energy forecasting; Providing on-line non-downloadable software for computing energy usage, savings, distribution, transmission, measurement, and forecasting; Providing on-line non-downloadable software utilizing artificial intelligence, and machine learning for use in connection with utilities services and assets, namely, for providing customers with access to utility account data and allowing customers to pay utility bills and for providing information, contextual prediction, personalization, predictive analytics, and analyzing data and metrics on energy usage, inter-connection of energy assets, renewable energy, energy savings, energy distribution, energy transmission, energy measurement, utilities assets, utilities repairs, route optimization, data optimization, customer service, energy finance, and energy forecasting; Providing online non-downloadable simulation software for modeling, planning, designing, operating, and optimizing utilities services, utilities assets, energy grids, energy inter-connections, renewable energy grids, energy distribution, energy transmission, energy measurements, and also for energy forecasting; Research and development of computer software; Consulting services in the fields of energy measurement to improve energy efficiency
09 - Appareils et instruments scientifiques et électriques
Produits et services
(1) Downloadable and recorded computer software for research, modeling, data collection, data ingestion, data storage, and simulations in the fields of biology, synthetic biology, pharmaceutical preparations, biotechnology, living systems, renewable materials, chemicals, organisms, and bioprocesses.
12.
SOLVENT-BASED PROCESSES FOR FUNCTIONALIZED MATERIALS
Methods of producing functionalized materials are provided. Porous particles are introduced to a functionalization mixture including a volatile solvent. The functionalization mixture includes an adsorbing moiety including polyethylenimine, an interaction moiety including a silane moiety, a polymer, a crosslinking agent, a chelating agent, or an antioxidant. Porous particles are characterized by a porosity distribution between 100 and 200 nanometers and a diameter distribution between 0.8 and 3 millimeters. Functionalized particles are created through deposition of the functionalization mixture on a surface of a porous particle to form a surface modification layer. Compositions and functionalized materials are also provided.
B01J 20/28 - Compositions absorbantes ou adsorbantes solides ou compositions facilitant la filtrationAbsorbants ou adsorbants pour la chromatographieProcédés pour leur préparation, régénération ou réactivation caractérisées par leur forme ou leurs propriétés physiques
Methods and systems for using multiple hyperspectral cameras sensitive to different wavelengths to predict characteristics of objects for further processing, including recycling, are described. The multiple hyperspectral images can be used to predict higher resolution spectra by using a trained machine learning model. The higher resolution spectra may be more easily analyzed to sort plastics into a recyclability category. The hyperspectral images may also be used to identify and analyze dark or black plastics, which are challenging for SWIR, MWIR, and other wavelengths. The machine learning model may also predict the base polymers and contaminants of plastic objects for recycling. The hyperspectral images may be used to predict recyclability and other characteristics using a trained machine learning model.
G01J 3/40 - Mesure de l'intensité des raies spectrales par détermination de la densité d'une photographie du spectreSpectrographie
G06V 10/56 - Extraction de caractéristiques d’images ou de vidéos relative à la couleur
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 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
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for improved image segmentation using hyperspectral imaging. In some implementations, a system obtains image data of a hyperspectral image, the image data comprising image data for each of multiple wavelength bands. The system accesses stored segmentation profile data for a particular object type that indicates a predetermined subset of the wavelength bands designated for segmenting different region types for images of an object of the particular object type. The system segments the image data into multiple regions using the predetermined subset of the wavelength bands specified in the stored segmentation profile data to segment the different region types. The system provides output data indicating the multiple regions and the respective region types of the multiple regions.
G06V 10/26 - Segmentation de formes dans le champ d’imageDécoupage ou fusion d’éléments d’image visant à établir la région de motif, p. ex. techniques de regroupementDétection d’occlusion
15.
SOLVENT-BASED PROCESSES FOR FUNCTIONALIZED MATERIALS
Methods of producing functionalized materials are provided. Porous particles are introduced to a functionalization mixture including a volatile solvent. The functionalization mixture includes an adsorbing moiety including polyethylenimine, an interaction moiety including a silane moiety, a polymer, a crosslinking agent, a chelating agent, or an antioxidant. Porous particles are characterized by a porosity distribution between 100 and 200 nanometers and a diameter distribution between 0.8 and 3 millimeters. Functionalized particles are created through deposition of the functionalization mixture on a surface of a porous particle to form a surface modification layer. Compositions and functionalized materials are also provided.
B01J 20/28 - Compositions absorbantes ou adsorbantes solides ou compositions facilitant la filtrationAbsorbants ou adsorbants pour la chromatographieProcédés pour leur préparation, régénération ou réactivation caractérisées par leur forme ou leurs propriétés physiques
B01D 53/02 - Séparation de gaz ou de vapeursRécupération de vapeurs de solvants volatils dans les gazÉpuration chimique ou biologique des gaz résiduaires, p. ex. gaz d'échappement des moteurs à combustion, fumées, vapeurs, gaz de combustion ou aérosols par adsorption, p. ex. chromatographie préparatoire en phase gazeuse
Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for template-based building design optimization for building projects. Constraints for a building project are identified. Building design templates that meet the constraints are identified in a design template library. Building design options for the building project are automatically determined, based on identified building design templates. The building design options for the building project are evaluated based on building performance metrics. Selected building design options are selected based on evaluated building design options. A building plan is automatically generated for the building project that includes building designs that include selected building design options.
G06F 30/13 - Conception architecturale, p. ex. conception architecturale assistée par ordinateur [CAAO] relative à la conception de bâtiments, de ponts, de paysages, d’usines ou de routes
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Research and development of new products; providing
information on product research and product development via
a website; providing information in the fields of technology
and product design and development; providing technological
information on the use of technology to solve international
problems via a website; design and testing for new product
development; scientific and technological research and
development services; research and development in the field
of computer software and hardware; research and development
in the field of software and technology using artificial
intelligence and machine learning; development of new
technology for others in the field of artificial
intelligence and machine learning; development of new
technology for others in the field of environmental
sustainability, software automation, supply chain logistics,
communications and Internet access, utility access and
monitoring, and bioengineering.
18.
SUBTERRANEAN PARAMETER SENSING SYSTEMS AND METHODS
A carbon dioxide (CO2) sequestration sensor system includes an underground sub-assembly including one or more sensors configured to detect at least one attribute associated with CO2 sequestration below a terranean surface; and an above-ground sub-assembly positionable on the terranean surface proximate the underground sub-assembly and including at least one controller communicably coupled to the one or more sensors.
G01N 33/00 - Recherche ou analyse des matériaux par des méthodes spécifiques non couvertes par les groupes
E21B 41/00 - Matériel ou accessoires non couverts par les groupes
E21B 47/117 - Détection de fuites, p. ex. du tubage, par test de pression
E21B 47/12 - Moyens pour la transmission de signaux de mesure ou signaux de commande du puits vers la surface, ou de la surface vers le puits, p. ex. pour la diagraphie pendant le forage
G01V 1/18 - Éléments récepteurs, p. ex. sismomètre, géophone
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating data items. One of the methods includes obtaining a conditioning input that characterizes a target seismic data item; and processing the conditioning input that characterizes the target seismic data item using a diffusion model that comprises a denoising neural network to generate the target seismic data item.
G01V 1/36 - Exécution de corrections statiques ou dynamiques sur des enregistrements, p. ex. correction de l'étalementÉtablissement d'une corrélation entre signaux sismiquesÉlimination des effets produits par un excès d'énergie
G06N 3/084 - Rétropropagation, p. ex. suivant l’algorithme du gradient
09 - Appareils et instruments scientifiques et électriques
Produits et services
Downloadable and recorded computer software for research, modeling, data collection, data ingestion, data storage, and simulations in the fields of biology, synthetic biology, pharmaceutical preparations, biotechnology, living systems, renewable materials, chemicals, organisms, and bioprocesses
Methods, systems, and apparatus are disclosed for electrical power grid visualization. A computer-implemented method includes: obtaining power grid data including different temporal and spatially dependent characteristics of a power grid, the characteristics including a first characteristic, a second characteristic, and a third characteristic; and generating a graphical user interface (GUI) representing a visualization of the power grid data. The GUI includes a line-diagram representation of power lines in the power grid overlaid on a map of a geographic region in which the power grid is located, the line-diagram including a plurality of line segments, wherein attributes of each line segment represent the power grid data at a particular spatial location of the power grid. The attributes include a time-changing thickness of the line segment representing the first characteristic; a plurality of time-changing directional arrows on the line segment representing the second characteristic; and a color shading representing the third characteristic.
H02J 13/00 - Circuits pour pourvoir à l'indication à distance des conditions d'un réseau, p. ex. un enregistrement instantané des conditions d'ouverture ou de fermeture de chaque sectionneur du réseauCircuits pour pourvoir à la commande à distance des moyens de commutation dans un réseau de distribution d'énergie, p. ex. mise en ou hors circuit de consommateurs de courant par l'utilisation de signaux d'impulsion codés transmis par le réseau
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training kinetic models on experimental data of biochemical pathways. In one aspect, a method comprises: receiving chemical reaction data for a biochemical pathway; automatically generating data defining a kinetic model of the biochemical pathway based on the chemical reaction data; obtaining experimental data for the biochemical pathway; training the kinetic model on the experimental data using a numerical optimization technique to optimize an objective function that measures a discrepancy between: (i) simulated data characterizing the biochemical pathway that is generated using the kinetic model, and (ii) the experimental data characterizing the biochemical pathway; and outputting the kinetic model of the biochemical pathway after training the set of kinetic model parameters.
G16C 20/10 - Analyse ou conception des réactions, des synthèses ou des procédés chimiques
G16B 5/00 - TIC spécialement adaptées à la modélisation ou aux simulations dans la biologie des systèmes, p. ex. réseaux de régulation génétique, réseaux d’interaction entre protéines ou réseaux métaboliques
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
(1) Downloadable AI software for assisting in real estate development, building construction, and architectural design, generating pre-development building designs, securing permitting and capital allocation for real estate projects, real estate marketing, identifying building locations and nature of real estate projects, and providing operative construction drawings; downloadable AI software for analyzing and compiling real estate, construction, and architectural data, generating and enhancing models, and generating text, images, audiovisual material, and document in response to prompts; downloadable software utilizing artificial intelligence for use in providing information and predictive recommendations on real estate development, building construction, and architectural design; downloadable computer chatbot software for simulating conversations; downloadable computer chatbot software for assisting in real estate development, building construction, and architectural design, generating pre-development building designs, securing permitting and capital allocation for real estate projects, real estate marketing, identifying building locations and nature of real estate projects, and providing operative construction drawings. (1) Business advisory and information services in the fields of architecture, real estate, interior design and urban planning design; providing business planning and marketing solutions for real estate professionals; real estate marketing analysis; real estate sales management; business research and data analysis services in the field of in the fields of architecture, interior design and urban planning design; business consulting services in the fields of architecture, real estate, interior design and urban planning design; data processing services in the fields of architecture, real estate, interior design and urban planning design; analyzing and compiling business data in the fields of architecture, real estate, interior design and urban planning design; compiling and analyzing statistics, data and other sources of information for business purposes in the fields of architecture, real estate, interior design and urban planning design.
(2) Providing online non-downloadable software for assisting in real estate development, building construction, and architectural design, generating pre-development building designs, securing permitting and capital allocation for real estate projects, real estate marketing, identifying building locations and nature of real estate projects, and providing operative construction drawings; Software as a Service (SaaS) services featuring software for assisting in real estate development, building construction, and architectural design, generating pre-development building designs, securing permitting and capital allocation for real estate projects, real estate marketing, identifying building locations and nature of real estate projects, and providing operative construction drawings; providing online non-downloadable AI software for analyzing and compiling real estate, construction, and architectural data, generating and enhancing models, and generating text, images, audiovisual material, and document in response to prompts; Software as a Service (SaaS) services featuring AI software for analyzing and compiling real estate, construction, and architectural data, generating and enhancing models, and generating text, images, audiovisual material, and document in response to prompts; providing online non-downloadable software utilizing artificial intelligence for use in providing information and predictive recommendations on real estate development, building construction, and architectural design; Software as a Service (SaaS) services featuring software utilizing artificial intelligence for use in providing information and predictive recommendations on real estate development, building construction, and architectural design; providing online non-downloadable computer chatbot software for simulating conversations; providing online non-downloadable computer chatbot software for assisting in real estate development, building construction, and architectural design, generating pre-development building designs, securing permitting and capital allocation for real estate projects, real estate marketing, identifying building locations and nature of real estate projects, and providing operative construction drawings; architectural services; residential and commercial building design.
24.
AUTOMATED KINETIC MODEL GENERATION FOR BIOCHEMICAL PATHWAYS
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training kinetic models on experimental data of biochemical pathways. In one aspect, a method comprises: receiving chemical reaction data for a biochemical pathway; automatically generating data defining a kinetic model of the biochemical pathway based on the chemical reaction data; obtaining experimental data for the biochemical pathway; training the kinetic model on the experimental data using a numerical optimization technique to optimize an objective function that measures a discrepancy between: (i) simulated data characterizing the biochemical pathway that is generated using the kinetic model, and (ii) the experimental data characterizing the biochemical pathway; and outputting the kinetic model of the biochemical pathway after training the set of kinetic model parameters.
G16B 5/00 - TIC spécialement adaptées à la modélisation ou aux simulations dans la biologie des systèmes, p. ex. réseaux de régulation génétique, réseaux d’interaction entre protéines ou réseaux métaboliques
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
Disclosed implementations relate to automating semantically-similar computing tasks across multiple contexts. In various implementations, an initial natural language input and a first plurality of actions performed using a first computer application may be used to generate a first task embedding and a first action embedding in action embedding space. An association between the first task embedding and first action embedding may be stored. Later, subsequent natural language input may be used to generate a second task embedding that is then matched to the first task embedding. Based on the stored association, the first action embedding may be identified and processed using a selected domain model to select actions to be performed using a second computer application. The selected domain model may be trained to translate between an action space of the second computer application and the action embedding space.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus
G06F 40/35 - Représentation du discours ou du dialogue
G06F 40/40 - Traitement ou traduction du langage naturel
G06F 40/58 - Utilisation de traduction automatisée, p. ex. pour recherches multilingues, pour fournir aux dispositifs clients une traduction effectuée par le serveur ou pour la traduction en temps réel
26.
MOLECULAR STRUCTURE TRANSFORMERS FOR PROPERTY PREDICTION
Computer-implemented methods may include accessing a multi-dimensional embedding space that supports relating embeddings of molecules to predicted values of a given property of the molecules. The method may also include identifying one or more points of interest within the embedding space based on the predicted values. Each of the one or more points of interest may include a set of coordinate values within the multi-dimensional embedding space and may be associated with a corresponding predicted value of the given property. The method may further include generating, for each of the one or more points of interest, a structural representation of a molecule by transforming the set of coordinate values included in the point of interest using a decoder network. The method may include outputting a result that identifies, for each of the one or more points of interest, the structural representation of the molecule corresponding to the point of interest.
C08J 11/16 - Récupération ou traitement des résidus des polymères par coupure des chaînes moléculaires des polymères ou rupture des liaisons de réticulation par voie chimique, p. ex. dévulcanisation par traitement avec une substance inorganique
C08J 11/10 - Récupération ou traitement des résidus des polymères par coupure des chaînes moléculaires des polymères ou rupture des liaisons de réticulation par voie chimique, p. ex. dévulcanisation
G16C 10/00 - Chimie théorique computationnelle, c.-à-d. TIC spécialement adaptées aux aspects théoriques de la chimie quantique, de la mécanique moléculaire, de la dynamique moléculaire ou similaires
G16C 20/10 - Analyse ou conception des réactions, des synthèses ou des procédés chimiques
G16C 20/20 - Identification d’entités moléculaires, de leurs parties ou de compositions chimiques
G16C 20/40 - Recherche de structures chimiques ou de données physicochimiques
G16C 20/70 - Apprentissage automatique, exploration de données ou chimiométrie
G16C 60/00 - Science informatique des matériaux, c.-à-d. TIC spécialement adaptées à la recherche des propriétés physiques ou chimiques de matériaux ou de phénomènes associés à leur conception, synthèse, traitement, caractérisation ou utilisation
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable AI software for assisting in real estate development, building construction, and architectural design, generating pre-development building designs, securing permitting and capital allocation for real estate projects, real estate marketing, identifying building locations and nature of real estate projects, and providing operative construction drawings; Downloadable AI software for analyzing and compiling real estate, construction, and architectural data, generating and enhancing models, and generating text, images, audiovisual material, and document in response to prompts; Downloadable software utilizing artificial intelligence for use in providing information and predictive recommendations on real estate development, building construction, and architectural design; Downloadable computer chatbot software for simulating conversations; Downloadable computer chatbot software for assisting in real estate development, building construction, and architectural design, generating pre-development building designs, securing permitting and capital allocation for real estate projects, real estate marketing, identifying building locations and nature of real estate projects, and providing operative construction drawings Business advisory and information services in the fields of architecture, real estate, interior design and urban planning design; Providing business planning and marketing solutions for real estate professionals; Real estate marketing analysis; Real estate sales management; Business research and data analysis services in the field of in the fields of architecture, interior design and urban planning design; Business consulting services in the fields of architecture, real estate, interior design and urban planning design; Data processing services in the fields of architecture, real estate, interior design and urban planning design; Analyzing and compiling business data in the fields of architecture, real estate, interior design and urban planning design; Compiling and analyzing statistics, data and other sources of information for business purposes in the fields of architecture, real estate, interior design and urban planning design Providing online non-downloadable software for assisting in real estate development, building construction, and architectural design, generating pre-development building designs, securing permitting and capital allocation for real estate projects, real estate marketing, identifying building locations and nature of real estate projects, and providing operative construction drawings; Software as a Service (SaaS) services featuring software for assisting in real estate development, building construction, and architectural design, generating pre-development building designs, securing permitting and capital allocation for real estate projects, real estate marketing, identifying building locations and nature of real estate projects, and providing operative construction drawings; Providing online non-downloadable AI software for analyzing and compiling real estate, construction, and architectural data, generating and enhancing models, and generating text, images, audiovisual material, and document in response to prompts; Software as a Service (SaaS) services featuring AI software for analyzing and compiling real estate, construction, and architectural data, generating and enhancing models, and generating text, images, audiovisual material, and document in response to prompts; Providing online non-downloadable software utilizing artificial intelligence for use in providing information and predictive recommendations on real estate development, building construction, and architectural design; Software as a Service (SaaS) services featuring software utilizing artificial intelligence for use in providing information and predictive recommendations on real estate development, building construction, and architectural design; Providing online non-downloadable computer chatbot software for simulating conversations; Providing online non-downloadable computer chatbot software for assisting in real estate development, building construction, and architectural design, generating pre-development building designs, securing permitting and capital allocation for real estate projects, real estate marketing, identifying building locations and nature of real estate projects, and providing operative construction drawings; Architectural services; Residential and commercial building design
Disclosed herein are systems and methods for objectively characterizing machine-learning models including receiving first training data formatted to be used in the training of a machine-learning model; receiving one or more challenge queries formatted to be run on the machine-learning model; generating, for the first training data, a plurality of associated training vectors that embed at least some of the first training data into a vector space; generating, for each of the one or more challenge queries, a plurality of associated challenge vectors that embed at least some of the challenge queries into the vector space; and determining, for each challenge query, a corresponding quality metric for the machine-learning model by determining a neighborhood density for each of the challenge queries in the vector space.
G06F 16/215 - Amélioration de la qualité des donnéesNettoyage des données, p. ex. déduplication, suppression des entrées non valides ou correction des erreurs typographiques
29.
ATTENTION GUIDING LAYER IN CONVOLUTIONAL NEURAL NETWORKS
Methods, systems, and apparatus for receiving a request for a prediction relevant to an object of interest (OOI) in the geographic region, providing an attention guiding layer based on a location of the OOI within the geographic layer, the attention guiding layer including a matrix of pixels, each pixel having an attention value assigned thereto, retrieving a set of layers representative of the geographic region, processing the set of layers and the attention guiding layer by a ML model to generate the prediction relevant to the OOI, the ML model including a convolutional neural network (CNN), and providing a representation of the prediction for display.
G06V 10/25 - Détermination d’une région d’intérêt [ROI] ou d’un volume d’intérêt [VOI]
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p. ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersectionsAnalyse de connectivité, p. ex. de composantes connectées
G06V 10/58 - Extraction de caractéristiques d’images ou de vidéos relative aux données hyperspectrales
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
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
G06V 20/70 - Étiquetage du contenu de scène, p. ex. en tirant des représentations syntaxiques ou sémantiques
G06V 20/52 - Activités de surveillance ou de suivi, p. ex. pour la reconnaissance d’objets suspects
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
30.
TECHNIQUES FOR USING INVERSE DESIGN FOR COMBINED OPTIMIZATION OF OPTICAL AND ELECTRICAL COMPONENTS IN AN OPTOELECTRONIC MODULATOR
In some embodiments, a computer-implemented method for creating a design for an optoelectronic modulator device is provided. A computing system determines an initial design that includes optical structural parameters and electrical structural parameters for a design region. The computing system simulates electrical performance based on the electrical structural parameters to adjust optical characteristics of the optical structural parameters. The computing system simulates optical performance of the optical structural parameters having the adjusted optical characteristics to generate a performance loss value. The computing system determines a loss metric based on the performance loss value. The computing system backpropagates the loss metric to determine a structural gradient. The computing system revises at least one of the optical structural parameters and the electrical structural parameters based at least in part on the structural gradient to create an updated initial design.
G02F 1/01 - Dispositifs ou dispositions pour la commande de l'intensité, de la couleur, de la phase, de la polarisation ou de la direction de la lumière arrivant d'une source lumineuse indépendante, p. ex. commutation, ouverture de porte ou modulationOptique non linéaire pour la commande de l'intensité, de la phase, de la polarisation ou de la couleur
G02F 1/025 - Dispositifs ou dispositions pour la commande de l'intensité, de la couleur, de la phase, de la polarisation ou de la direction de la lumière arrivant d'une source lumineuse indépendante, p. ex. commutation, ouverture de porte ou modulationOptique non linéaire pour la commande de l'intensité, de la phase, de la polarisation ou de la couleur basés sur des éléments à semi-conducteurs ayant des barrières de potentiel, p. ex. une jonction PN ou PIN dans une structure de guide d'ondes optique
G06F 30/20 - Optimisation, vérification ou simulation de l’objet conçu
G06F 119/02 - Analyse de fiabilité ou optimisation de fiabilitéAnalyse de défaillance, p. ex. performance dans le pire scénario, analyse du mode de défaillance et de ses effets [FMEA]
31.
TECHNIQUES FOR USING INVERSE DESIGN FOR COMBINED OPTIMIZATION OF OPTICAL AND ELECTRICAL COMPONENTS IN AN OPTOELECTRONIC MODULATOR
In some embodiments, a computer-implemented method for creating a design for an optoelectronic modulator device is provided. A computing system determines an initial design that includes optical structural parameters and electrical structural parameters for a design region. The computing system simulates electrical performance based on the electrical structural parameters to adjust optical characteristics of the optical structural parameters. The computing system simulates optical performance of the optical structural parameters having the adjusted optical characteristics to generate a performance loss value. The computing system determines a loss metric based on the performance loss value. The computing system backpropagates the loss metric to determine a structural gradient. The computing system revises at least one of the optical structural parameters and the electrical structural parameters based at least in part on the structural gradient to create an updated initial design.
An integrated geomaterials preparation method including receiving, through an API of an integrated geomaterials preparation platform, a raw material request and a set of end-product parameters, determining, from the set of end-product parameters, required characteristics for at least one raw material ingredient to an end product to meet the raw material request, obtaining raw material sensor data from a plurality of raw material sensor systems, identifying, from the raw material sensor data, a particular raw material having characteristics similar to the required characteristics, where each sensor system is configured to scan and characterize raw materials, generating, using the characteristics of the particular raw material, operational parameters for geomaterial processing equipment to produce a raw material ingredient to meet the raw material request, and providing, the operational parameters to the geomaterial processing equipment, which when executed by the geomaterial processing equipment cause the geomaterial processing equipment to execute the operational parameters.
An integrated geomaterials preparation method including receiving, through an API of an integrated geomaterials preparation platform, a raw material request and a set of end-product parameters, determining, from the set of end-product parameters, required characteristics for at least one raw material ingredient to an end product to meet the raw material request, obtaining raw material sensor data from a plurality of raw material sensor systems, identifying, from the raw material sensor data, a particular raw material having characteristics similar to the required characteristics, where each sensor system is configured to scan and characterize raw materials, generating, using the characteristics of the particular raw material, operational parameters for geomaterial processing equipment to produce a raw material ingredient to meet the raw material request, and providing, the operational parameters to the geomaterial processing equipment, which when executed by the geomaterial processing equipment cause the geomaterial processing equipment to execute the operational parameters.
A thermally regulated photonic system includes a photonic component, a sensor adapted to measure a temperature related to the photonic component or a power output of the photonic component and generate a sensor value that is indicative of the temperature or the power output, a heat distribution system thermally coupled to the photonic component and adapted to generate and distribute heat to the photonic component, and a controller coupled to the sensor and the heat distribution system in a feedback loop configuration to thermally regulate the photonic component based upon the sensor value.
G02B 6/293 - Moyens de couplage optique ayant des bus de données, c.-à-d. plusieurs guides d'ondes interconnectés et assurant un système bidirectionnel par nature en mélangeant et divisant les signaux avec des moyens de sélection de la longueur d'onde
A thermally regulated photonic system includes a photonic component, a sensor adapted to measure a temperature related to the photonic component or a power output of the photonic component and generate a sensor value that is indicative of the temperature or the power output, a heat distribution system thermally coupled to the photonic component and adapted to generate and distribute heat to the photonic component, and a controller coupled to the sensor and the heat distribution system in a feedback loop configuration to thermally regulate the photonic component based upon the sensor value.
G02B 6/12 - Guides de lumièreDétails de structure de dispositions comprenant des guides de lumière et d'autres éléments optiques, p. ex. des moyens de couplage du type guide d'ondes optiques du genre à circuit intégré
G02F 1/01 - Dispositifs ou dispositions pour la commande de l'intensité, de la couleur, de la phase, de la polarisation ou de la direction de la lumière arrivant d'une source lumineuse indépendante, p. ex. commutation, ouverture de porte ou modulationOptique non linéaire pour la commande de l'intensité, de la phase, de la polarisation ou de la couleur
G02B 6/42 - Couplage de guides de lumière avec des éléments opto-électroniques
36.
FUNCTIONALIZED MATERIALS FOR CARBON CAPTURE AND SYSTEMS THEREOF
The present disclosure relates to a functionalized material, which may optionally be employed as a sorbent for carbon dioxide, as well as methods of making such materials and systems of using such materials. The processes, methods, and systems herein can be used for the separation of carbon dioxide from fluid streams.
B01D 53/83 - Procédés en phase solide avec des réactifs en mouvement
B01D 53/96 - Régénération, réactivation ou recyclage des réactifs
B01J 20/10 - Compositions absorbantes ou adsorbantes solides ou compositions facilitant la filtrationAbsorbants ou adsorbants pour la chromatographieProcédés pour leur préparation, régénération ou réactivation contenant une substance inorganique contenant de la silice ou un silicate
B01J 20/22 - Compositions absorbantes ou adsorbantes solides ou compositions facilitant la filtrationAbsorbants ou adsorbants pour la chromatographieProcédés pour leur préparation, régénération ou réactivation contenant une substance organique
B01J 20/28 - Compositions absorbantes ou adsorbantes solides ou compositions facilitant la filtrationAbsorbants ou adsorbants pour la chromatographieProcédés pour leur préparation, régénération ou réactivation caractérisées par leur forme ou leurs propriétés physiques
B01J 20/30 - Procédés de préparation, de régénération ou de réactivation
A polarization rotating and beam splitting photonic device includes a planar waveguide having an input port and output ports disposed in or on a multi-layer semiconductor stack and a polarization rotating and beam splitting components integrated into the planar waveguide. The polarization rotating component includes a first irregular pattern of at least two materials having different refractive indexes. The first irregular pattern is shaped to rotate at least a portion of an optical signal received via the input port from a transverse magnetic (TM) polarization to a transverse electric (TE) polarization. The beam splitting component includes a second irregular pattern shaped to split the optical signal between the output ports. The first and second irregularly shaped patterns are optically coupled and collectively shaped to receive input TE and TM signals multiplexed on the optical signal at the input port and generate output TE signals demultiplexed on the output ports.
A polarization rotating and beam splitting photonic device includes a planar waveguide having an input port and output ports disposed in or on a multi-layer semiconductor stack and a polarization rotating and beam splitting components integrated into the planar waveguide. The polarization rotating component includes a first irregular pattern of at least two materials having different refractive indexes. The first irregular pattern is shaped to rotate at least a portion of an optical signal received via the input port from a transverse magnetic (TM) polarization to a transverse electric (TE) polarization. The beam splitting component includes a second irregular pattern shaped to split the optical signal between the output ports. The first and second irregularly shaped patterns are optically coupled and collectively shaped to receive input TE and TM signals multiplexed on the optical signal at the input port and generate output TE signals demultiplexed on the output ports.
G02B 6/126 - Guides de lumièreDétails de structure de dispositions comprenant des guides de lumière et d'autres éléments optiques, p. ex. des moyens de couplage du type guide d'ondes optiques du genre à circuit intégré utilisant des effets de polarisation
G02B 6/125 - Courbures, branchements ou intersections
G02B 6/12 - Guides de lumièreDétails de structure de dispositions comprenant des guides de lumière et d'autres éléments optiques, p. ex. des moyens de couplage du type guide d'ondes optiques du genre à circuit intégré
G02B 27/28 - Systèmes ou appareils optiques non prévus dans aucun des groupes , pour polariser
39.
GENERATING BOUNDING BOXES FOR GEOLOCALIZING OBLIQUE AERIAL IMAGERY
Methods, systems, and apparatus for receiving a first image file recording a first image and a first set of metadata associated with the first image, determining that the first image depicts a horizon, and in response, providing a modified first set of metadata by applying a visibility radius to a projection of the Earth depicted in the first image, determining a tangent line based on the visibility radius, and adjusting a height of the first image based on the tangent line to provide a modified height in the modified first set of metadata, and outputting a first geographic features file that is generated using the modified first set of metadata, the first geographic features file including data representing one or more geographic features represented in the first image file.
Methods, systems, and apparatus for receiving an image file recording an image and a set of metadata, determining a search space based on one or more of at least a portion of the set of metadata and auxiliary data, generating a set of candidate images based on the search space, identifying a candidate image in the set of candidate images as a best matching image relative to the image, the candidate image being associated with a set of candidate metadata, providing a set of augmented metadata for the image based on the set of metadata and the set of candidate metadata, the set of augmented metadata including at least a portion of the set of candidate metadata, and outputting a geographic features file that is generated using the set of augmented metadata, the geographic features file including data representing one or more geographic features represented in the image file.
G06F 16/58 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
G06F 16/587 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des informations géographiques ou spatiales, p. ex. la localisation
41.
TOWARDS PREDICTION OF GEOMATERIAL PROPERTIES POST-PROCESSING VIA HIGH-THROUGHPUT CHEMICAL AND SPATIAL CHARACTERIZATION
Methods, systems, and apparatus, including computer programs encoded on a storage device, for determining characteristics of particles are disclosed. A system includes a conveyor belt, wherein a first section of the conveyor belt comprises one or more mechanisms arranged to create environmental conditions favorable to sensor reading. The system includes a sensor rig located proximate to the first section of the conveyor belt comprising a plurality of different types of sensors. The system includes a controller configured to: obtain measurement data from the plurality of different types of sensors; apply the measurement data to a machine learning model configured to determine surface chemical characteristics of particles given measurement data; and output the surface chemical characteristics of particles from the machine learning model to one or more components along the conveyor belt.
Disclosed herein are systems and methods for objectively characterizing machine-learning models including receiving first training data formatted to be used in the training of a machine-learning model; receiving one or more challenge queries formatted to be run on the machine-learning model; generating, for the first training data, a plurality of associated training vectors that embed at least some of the first training data into a vector space; generating, for each of the one or more challenge queries, a plurality of associated challenge vectors that embed at least some of the challenge queries into the vector space; and determining, for each challenge query, a corresponding quality metric for the machine-learning model by determining a neighborhood density for each of the challenge queries in the vector space.
The present disclosure relates to a method and system for acquiring and processing large unlabeled dataset of images to train an embedding model using a self-supervision technique, which may then be used to generate image embeddings with reduced dimensions for any downstream task or model. The downstream model can be a simple model and can be trained efficiently using a small, labeled training dataset as the embedding model may distill important information from the images of the small, labeled training dataset. According to present disclosure, the downstream task or model may include predicting a material category or quantity of a target material of interest in an image that captures (part or all of) one or more objects on a feedstock or a waste stream. In some instances, the image may correspond to a hyperspectral image that is collected using a camera system.
G06T 1/00 - Traitement de données d'image, d'application générale
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
44.
GENERATING BOUNDING BOXES FOR GEOLOCALIZING OBLIQUE AERIAL IMAGERY
Methods, systems, and apparatus for receiving a first image file recording a first image and a first set of metadata associated with the first image, determining that the first image depicts a horizon, and in response, providing a modified first set of metadata by applying a visibility radius to a projection of the Earth depicted in the first image, determining a tangent line based on the visibility radius, and adjusting a height of the first image based on the tangent line to provide a modified height in the modified first set of metadata, and outputting a first geographic features file that is generated using the modified first set of metadata, the first geographic features file including data representing one or more geographic features represented in the first image file.
Computer-implemented techniques may include identifying a polymer for decomposition. For an ionic liquid, one or more properties corresponding to the polymer is accessed. One or more properties characterize a reaction between the polymer and the ionic liquid. A value of the property is accessed using a quantum-mechanical or thermodynamical method. A bond string and position (BSP) representation of a molecule of the ionic liquid is determined. An embedded representation of the ionic liquid is determined based on the BSP representation. A relationship between BSP representations of molecules and the one or more properties is generated. An ionic liquid is identified as a prospect for depolymerizing the specific polymer based on the relationship. An identification of the ionic liquid is output.
C08J 11/16 - Récupération ou traitement des résidus des polymères par coupure des chaînes moléculaires des polymères ou rupture des liaisons de réticulation par voie chimique, p. ex. dévulcanisation par traitement avec une substance inorganique
C08J 11/10 - Récupération ou traitement des résidus des polymères par coupure des chaînes moléculaires des polymères ou rupture des liaisons de réticulation par voie chimique, p. ex. dévulcanisation
G16C 10/00 - Chimie théorique computationnelle, c.-à-d. TIC spécialement adaptées aux aspects théoriques de la chimie quantique, de la mécanique moléculaire, de la dynamique moléculaire ou similaires
G16C 20/10 - Analyse ou conception des réactions, des synthèses ou des procédés chimiques
G16C 20/20 - Identification d’entités moléculaires, de leurs parties ou de compositions chimiques
G16C 20/40 - Recherche de structures chimiques ou de données physicochimiques
G16C 20/70 - Apprentissage automatique, exploration de données ou chimiométrie
G16C 60/00 - Science informatique des matériaux, c.-à-d. TIC spécialement adaptées à la recherche des propriétés physiques ou chimiques de matériaux ou de phénomènes associés à leur conception, synthèse, traitement, caractérisation ou utilisation
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
(1) Research and development of new products; providing information on product research and product development via a website; providing information in the fields of technology and product design and development; providing technological information on the use of technology to solve international problems via a website; design and testing for new product development; scientific and technological research and development services; research and development in the field of computer software and hardware; research and development in the field of software and technology using artificial intelligence and machine learning; development of new technology for others in the field of artificial intelligence and machine learning; development of new technology for others in the field of environmental sustainability, software automation, supply chain logistics, communications and Internet access, utility access and monitoring, and bioengineering.
Techniques for determining a mineralogy of a portion of a drainage basin include identifying topography data associated with a drainage basin comprising at least one body of water; identifying weather data associated with the drainage basin; identifying first sensor data associated with a first water sensor installed in the drainage basin; identifying second sensor data associated with a second water sensor that is located downstream of the first water sensor in the drainage basin; providing the first sensor data, second sensor data, topography data, and weather data as input to a machine learning algorithm; and determining, by the machine learning algorithm, a mineralogy of a portion of the drainage basin.
G01C 13/00 - Géodésie spécialement adaptée à l'eau libre, p. ex. à la mer, aux lacs, aux rivières ou aux canaux
G01N 21/31 - 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
This specification is generally directed to techniques for robust natural language (NL) based control of computer applications. In many implementations, the NL control is at least selectively interactive in that the user feedback input is solicited, and received, in resolving action(s), resolving action set(s), generating domain specific knowledge, and/or in providing feedback on implemented action set(s). The user feedback input can be utilized in further training of machine learning model(s) utilized in the NL based control of the computer applications.
G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect
G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
Methods, systems, and apparatus, including computer programs encoded on a storage device, for protecting an electrical grid are disclosed. A method includes obtaining electrical grid data corresponding to grid reliability factors and grid safety factors; determining, based on an analysis of the grid reliability factors and the grid safety factors, one or more operating parameters for at least one electrical protection device; and controlling the at least one electrical protection device based on the one or more operating parameters.
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for identifying wildfire in satellite imagery. In some implementations, a server obtains a satellite image of a geographic region and a date corresponding to when the satellite image was generated. The server determines a number of pixels in the satellite image that are indicated as on fire. The server obtains satellite imagery of the geographic region from before the date. The server generates a statistical distribution from the satellite imagery. The server determines a likelihood that the satellite image illustrates fire based on a comparison of the determined number of pixels in the satellite image that are indicated as on fire to the generated statistical distribution. The server can compare the determined likelihood to a threshold. In response to comparing the determined likelihood to the threshold, the server provides an indication that the satellite image illustrates fire.
This disclosure describes systems and methods for multi-modal search-based object detection and electric grid object search. Annotations and bounding boxes for images in an image database are determined. A first subset of images is determined from the images that share annotations. A textual token representing the first subset of images is generated and stored in a search index. A second subset of images that share visual features is determined from image pixels enclosed by the bounding boxes. An image token is generated based on the second subset of images and the shared visual features. A user interface configured to receive a search query input is provided for display on a user device. Search tokens are generated based on the search query input. A candidate image is identified and provided for display within the user interface at a position within a respective region of a geographic map of an electric grid.
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
G06F 16/58 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
G06F 16/587 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des informations géographiques ou spatiales, p. ex. la localisation
52.
STATE TRANSITION MATRIX-BASED POWER SYSTEM SIMULATION
Methods, systems, and apparatus, including medium-encoded computer program products, for electrical power grid simulation. One of the methods includes obtaining a state-transition matrix model of an electrical power grid and executing a simulation of electric power grid behaviors by executing the state-transition matrix model using a parallel processing device that includes multiple cores.
G06F 30/367 - Vérification de la conception, p. ex. par simulation, programme de simulation avec emphase de circuit intégré [SPICE], méthodes directes ou de relaxation
Functionalized and crosslinked material, which may optionally be employed as a sorbent, as well as methods of making such materials and systems of using such materials are provided. The processes, methods, systems and materials herein can be used for the separation of carbon dioxide from fluid streams. In one aspect, a method of forming functionalized crosslinked particles comprises introducing at least a portion of a surface of each porous particle in at least a subset of a plurality of porous particles to a crosslinking agent and a first reagent comprising at least one adsorbing moiety. Examples of adsorbing moiety include silane-functionalized amines, amino-functionalized silanes (aminosilane), and polyamines. In some aspects the method further comprises introducing the porous particles to a second reagent comprising at least one interaction moiety such as a silane-functionalized amine, amino-functionalized silane (aminosilane), or polyamine. Examples of crosslinking agent include dialdehyde, diisocyanates, dihaloalkane, diepoxide and dianhydrides.
B01J 20/22 - Compositions absorbantes ou adsorbantes solides ou compositions facilitant la filtrationAbsorbants ou adsorbants pour la chromatographieProcédés pour leur préparation, régénération ou réactivation contenant une substance organique
B01J 20/28 - Compositions absorbantes ou adsorbantes solides ou compositions facilitant la filtrationAbsorbants ou adsorbants pour la chromatographieProcédés pour leur préparation, régénération ou réactivation caractérisées par leur forme ou leurs propriétés physiques
B01J 20/30 - Procédés de préparation, de régénération ou de réactivation
B01D 53/02 - Séparation de gaz ou de vapeursRécupération de vapeurs de solvants volatils dans les gazÉpuration chimique ou biologique des gaz résiduaires, p. ex. gaz d'échappement des moteurs à combustion, fumées, vapeurs, gaz de combustion ou aérosols par adsorption, p. ex. chromatographie préparatoire en phase gazeuse
54.
NEGATIVE EMISSIONS USING INORGANIC WASTE RECYCLING
Provided herein are methods and systems for achieving ocean alkalinity enhancement (OAE), which provides a means of reducing atmospheric carbon dioxide levels, through electrolytic salt splitting. Treatment of ocean waters with the alkaline portion of salt splitting and treatment of inorganic waste with the acid portion of the salt splitting provide a means of achieving OAE without adding mineral content from land while at the same time providing a means of recycling inorganic waste in the form of recycled concrete aggregates.
C02F 1/461 - Traitement de l'eau, des eaux résiduaires ou des eaux d'égout par des procédés électrochimiques par électrolyse
C02F 103/08 - Eau de mer, p. ex. pour le dessalement
C02F 103/12 - Nature de l'eau, des eaux résiduaires ou des eaux ou boues d'égout à traiter provenant des industries des silicates ou des céramiques, p. ex. eaux résiduaires provenant des usines du ciment ou du verre
C04B 18/00 - Emploi de matières agglomérées, de résidus ou de déchets comme charges pour mortiers, béton ou pierre artificielleTraitement de matières agglomérées, de résidus ou de déchets, spécialement adapté pour renforcer leurs propriétés de charge, dans les mortiers, le béton ou la pierre artificielle
This disclosure describes systems and methods for multi-modal search-based object detection and electric grid object search. Annotations and bounding boxes for images in an image database are determined. A first subset of images is determined from the images that share annotations. A textual token representing the first subset of images is generated and stored in a search index. A second subset of images that share visual features is determined from image pixels enclosed by the bounding boxes. An image token is generated based on the second subset of images and the shared visual features. A user interface configured to receive a search query input is provided for display on a user device. Search tokens are generated based on the search query input. A candidate image is identified and provided for display within the user interface at a position within a respective region of a geographic map of an electric grid.
A method for training a machine learning model (MLM) to predict the activity of a protein is described herein. In an example, a method involves accessing a set of training data comprising labeled examples with known activity levels. A large language model is used to generate synthetic examples of each labeled example by incorporating each possible amino acid (AA) mutation at each AA position in the labeled example and predicting the probability each AA mutation has of replacing the original AA. Based on a predetermined cutoff, a subset of negative synthetic examples that comprises at least one AA mutation with the lowest probability of being incorporated are selected. An augmented training dataset is generated and a MLM is trained, using the training data and the augmented training data set, by performing iterative operations to find a set of parameters that jointly minimize the sum of at least two loss functions.
G16B 40/00 - TIC spécialement adaptées aux biostatistiquesTIC spécialement adaptées à l’apprentissage automatique ou à l’exploration de données liées à la bio-informatique, p. ex. extraction de connaissances ou détection de motifs
G16B 30/00 - TIC spécialement adaptées à l’analyse de séquences impliquant des nucléotides ou des aminoacides
57.
2X2 PHOTONIC SPLITTER USING MODE CONVERTING Y-JUNCTIONS
A 2×2 photonic splitter includes two mode converting Y-junctions. A first stage mode converting Y-junction includes input branch ports adapted to receive an input optical signal propagating in a fundamental spatial mode at either of the input branch ports, a first trunk port, and a first mode converting region. The first mode converting region is adapted to convert at least a first power portion of the fundamental spatial mode of the input optical signal when received via at least one of the input branch ports to a higher order spatial mode at the first trunk port. The second stage mode converting Y-junction includes output branch ports adapted to emit output optical signals having the fundamental spatial mode, a second trunk port, and a second mode converting region optically coupling the output branch ports to the second trunk port. A connected trunk section photonically links the trunk ports.
G02B 6/28 - Moyens de couplage optique ayant des bus de données, c.-à-d. plusieurs guides d'ondes interconnectés et assurant un système bidirectionnel par nature en mélangeant et divisant les signaux
58.
POWER GRID SIMULATION WITH REDUCED COMPONENT MODELS
Methods, systems, and apparatus, including medium-encoded computer program products that perform operations that include obtaining one or more physical parameters and one or more predetermined operating conditions for a component to be connected to the electric power grid at a predetermined grid connection point. And, obtaining training data characterizing the component; generating, based on the obtained training data, physical parameters and one or more predetermined operating conditions, a reduced order simulator of the component, where the reduced order model is trained to simulate the behavior of the component at the predetermined connection point under the predetermined operating conditions.
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
A 2x2 photonic splitter includes two mode converting Y-junctions. A first stage mode converting Y-junction includes input branch ports adapted to receive an input optical signal propagating in a fundamental spatial mode at either of the input branch ports, a first trunk port, and a first mode converting region. The first mode converting region is adapted to convert at least a first power portion of the fundamental spatial mode of the input optical signal when received via at least one of the input branch ports to a higher order spatial mode at the first trunk port. The second stage mode converting Y-junction includes output branch ports adapted to emit output optical signals having the fundamental spatial mode, a second trunk port, and a second mode converting region optically coupling the output branch ports to the second trunk port. A connected trunk section photonically links the trunk ports.
G02B 6/28 - Moyens de couplage optique ayant des bus de données, c.-à-d. plusieurs guides d'ondes interconnectés et assurant un système bidirectionnel par nature en mélangeant et divisant les signaux
G02B 6/293 - Moyens de couplage optique ayant des bus de données, c.-à-d. plusieurs guides d'ondes interconnectés et assurant un système bidirectionnel par nature en mélangeant et divisant les signaux avec des moyens de sélection de la longueur d'onde
60.
LARGE LANGUAGE MODEL DRIVEN DATA AUGMENTATION FOR PROTEIN MACHINE LEARNING
A method for training a machine learning model (MLM) to predict the activity of a protein is described herein. In an example, a method involves accessing a set of training data comprising labeled examples with known activity levels. A large language model is used to generate synthetic examples of each labeled example by incorporating each possible amino acid (AA) mutation at each AA position in the labeled example and predicting the probability each AA mutation has of replacing the original AA. Based on a predetermined cutoff, a subset of negative synthetic examples that comprises at least one AA mutation with the lowest probability of being incorporated are selected. An augmented training dataset is generated and a MLM is trained, using the training data and the augmented training data set, by performing iterative operations to find a set of parameters that jointly minimize the sum of at least two loss functions.
Disclosed herein are methods, and compositions produced using the methods, including introducing porous substrate particles and a first reagent comprising a polymer to a solvent to provide a plurality of coated particles; and introducing a second reagent comprising a polymeric amine and a third reagent comprising a silane moiety and an amine moiety to the coated particles, thereby providing a plurality of functionalized, coated particles.
B01J 20/28 - Compositions absorbantes ou adsorbantes solides ou compositions facilitant la filtrationAbsorbants ou adsorbants pour la chromatographieProcédés pour leur préparation, régénération ou réactivation caractérisées par leur forme ou leurs propriétés physiques
B01D 53/04 - Séparation de gaz ou de vapeursRécupération de vapeurs de solvants volatils dans les gazÉpuration chimique ou biologique des gaz résiduaires, p. ex. gaz d'échappement des moteurs à combustion, fumées, vapeurs, gaz de combustion ou aérosols par adsorption, p. ex. chromatographie préparatoire en phase gazeuse avec adsorbants fixes
22 from fluid streams. In one aspect, the disclosed materials are synthesized by forming coated particles through the introduction of porous particles, such as silica, to a first reagent comprising a polymer. Then the functionalized material is formed as functionalized coated particles by the introduction of a second reagent comprising at least one adsorbing moiety to the surfaces of the coated particles. Formation of the functionalized material is in the presence of a chelating agent, antioxidant, and/or crosslinker. In some instances, formation of the functionalized material is further in the presence of a third reagent comprising an interaction moiety that is incorporated into the functionalized coated particles.
B01J 20/22 - Compositions absorbantes ou adsorbantes solides ou compositions facilitant la filtrationAbsorbants ou adsorbants pour la chromatographieProcédés pour leur préparation, régénération ou réactivation contenant une substance organique
B01J 20/10 - Compositions absorbantes ou adsorbantes solides ou compositions facilitant la filtrationAbsorbants ou adsorbants pour la chromatographieProcédés pour leur préparation, régénération ou réactivation contenant une substance inorganique contenant de la silice ou un silicate
B01J 20/28 - Compositions absorbantes ou adsorbantes solides ou compositions facilitant la filtrationAbsorbants ou adsorbants pour la chromatographieProcédés pour leur préparation, régénération ou réactivation caractérisées par leur forme ou leurs propriétés physiques
B01J 20/30 - Procédés de préparation, de régénération ou de réactivation
B01D 53/02 - Séparation de gaz ou de vapeursRécupération de vapeurs de solvants volatils dans les gazÉpuration chimique ou biologique des gaz résiduaires, p. ex. gaz d'échappement des moteurs à combustion, fumées, vapeurs, gaz de combustion ou aérosols par adsorption, p. ex. chromatographie préparatoire en phase gazeuse
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for designing a multimodal photonic component. In one aspect, a method includes defining a loss function within a simulation space including multiple voxels and encompassing features of the multimodal photonic component. The loss function corresponds to a target output mode profile for an input mode profile, where the target output mode profile includes a relationship between a set of operating conditions and one or more supported modes of the multimodal photonic component at a particular operative wavelength. The initial structure is defined for one or more features, where at least some of the voxels corresponding to features have a dimension smaller than a smallest operative wavelength of the multimodal photonic component, and values for structural parameters for the features are determined so that a loss according to the loss function is within a threshold loss.
G02B 27/00 - Systèmes ou appareils optiques non prévus dans aucun des groupes ,
G06F 30/23 - Optimisation, vérification ou simulation de l’objet conçu utilisant les méthodes des éléments finis [MEF] ou les méthodes à différences finies [MDF]
Functionalized and crosslinked material, which may optionally be employed as a sorbent, as well as methods of making such materials and systems of using such materials are provided. The processes, methods, systems and materials herein can be used for the separation of carbon dioxide from fluid streams. In one aspect, a method of forming functionalized crosslinked particles comprises introducing at least a portion of a surface of each porous particle in at least a subset of a plurality of porous particles to a crosslinking agent and a first reagent comprising at least one adsorbing moiety. Examples of adsorbing moiety include silane-functionalized amines, amino-functionalized silanes (aminosilane), and polyamines. In some aspects the method further comprises introducing the porous particles to a second reagent comprising at least one interaction moiety such as a silane-functionalized amine, amino-functionalized silane (aminosilane), or polyamine. Examples of crosslinking agent include dialdehyde, diisocyanates, dihaloalkane, diepoxide and dianhydrides.
B01J 20/28 - Compositions absorbantes ou adsorbantes solides ou compositions facilitant la filtrationAbsorbants ou adsorbants pour la chromatographieProcédés pour leur préparation, régénération ou réactivation caractérisées par leur forme ou leurs propriétés physiques
Disclosed herein are methods, and compositions produced using the methods, including introducing porous substrate particles and a first reagent comprising a polymer to a solvent to provide a plurality of coated particles; and introducing a second reagent comprising a polymeric amine and a third reagent comprising a silane moiety and an amine moiety to the coated particles, thereby providing a plurality of functionalized, coated particles.
B01J 20/30 - Procédés de préparation, de régénération ou de réactivation
B01J 20/10 - Compositions absorbantes ou adsorbantes solides ou compositions facilitant la filtrationAbsorbants ou adsorbants pour la chromatographieProcédés pour leur préparation, régénération ou réactivation contenant une substance inorganique contenant de la silice ou un silicate
B01J 20/28 - Compositions absorbantes ou adsorbantes solides ou compositions facilitant la filtrationAbsorbants ou adsorbants pour la chromatographieProcédés pour leur préparation, régénération ou réactivation caractérisées par leur forme ou leurs propriétés physiques
Functionalized materials that act as sorbent, as well as methods of making such materials and systems of using such materials, are provided. The disclosed processes, methods, and materials can be used for the separation of CO2 from fluid streams. In one aspect, the disclosed materials are synthesized by forming coated particles through the introduction of porous particles, such as silica, to a first reagent comprising a polymer. Then the functionalized material is formed as functionalized coated particles by the introduction of a second reagent comprising at least one adsorbing moiety to the surfaces of the coated particles. Formation of the functionalized material is in the presence of a chelating agent, antioxidant, and/or crosslinker. In some instances, formation of the functionalized material is further in the presence of a third reagent comprising an interaction moiety that is incorporated into the functionalized coated particles.
B01D 53/04 - Séparation de gaz ou de vapeursRécupération de vapeurs de solvants volatils dans les gazÉpuration chimique ou biologique des gaz résiduaires, p. ex. gaz d'échappement des moteurs à combustion, fumées, vapeurs, gaz de combustion ou aérosols par adsorption, p. ex. chromatographie préparatoire en phase gazeuse avec adsorbants fixes
B01J 20/28 - Compositions absorbantes ou adsorbantes solides ou compositions facilitant la filtrationAbsorbants ou adsorbants pour la chromatographieProcédés pour leur préparation, régénération ou réactivation caractérisées par leur forme ou leurs propriétés physiques
B01J 20/30 - Procédés de préparation, de régénération ou de réactivation
A system for transferring heat between fluid and a bulk solid. The system includes a plurality of heat exchanger units, each heat exchanger unit comprising: an annular structure including an inner shell and an outer shell; and a first plate and a second plate defining therebetween a conduit for transporting the fluid, wherein the conduit forms a spiral around the inner shell, the spiral extending from the inner shell towards the outer shell, a space between turns of the spiral defining a channel for passage of the bulk solid. The inner shell defines a cylindrical annulus of the annular structure, an axis of the cylindrical annulus being aligned with the direction of gravity during operation. The bulk solid comprises a sorbent material configured to adsorb carbon dioxide from air. The fluid comprises a cooling fluid or a heating fluid.
F28D 9/04 - Appareils échangeurs de chaleur comportant des ensembles de canalisations fixes en forme de plaques ou de laminés pour les deux sources de potentiel calorifique, ces sources étant en contact chacune avec un côté de la paroi d'une canalisation les canalisations étant formées par des plaques ou des laminés enroulés en spirale
F28D 7/04 - Appareils échangeurs de chaleur comportant des ensembles de canalisations tubulaires fixes pour les deux sources de potentiel calorifique, ces sources étant en contact chacune avec un côté de la paroi d'une canalisation les canalisations étant enroulées en spirale
F25B 15/16 - Machines, installations ou systèmes à sorption, à marche continue, p. ex. à absorption utilisant le cycle de désorption
A method for electrical grid service monitoring and valuation includes detecting a connection of a grid asset to an electric grid; receiving, from the grid asset, a communication indicating operating parameters for the grid asset; adding, to a database of grid assets, an identifier for the grid asset and the operating parameters; and simulating conditions of the electric grid based on data corresponding to a plurality of grid assets, the data being stored in the database; obtaining data indicating a status of the grid asset; determining that the grid asset is performing a grid service; obtaining an estimated value of the grid service using simulation results; obtaining energy market data indicating a market value of energy provided by the electric grid; and determining a value for the grid service performed based on (a) the estimated value of the grid service and (b) the energy market data.
Methods, systems, and apparatus, including medium-encoded computer program products, for transformer connection mapping in an operating electric power grid. The system can determine that a first utility meter is fed by a transformer in an electrical power distribution network based on a geographic distance between the first utility meter and the transformer as determined from non-electrical data. The system can obtain first electrical measurements from the first utility meter at predetermined time intervals and second electrical measurements from a second utility meter at the predetermined time intervals. The system can determine a likelihood that the second utility meter is fed by the transformer by, at least, performing a time-based correlation between the first electrical measurements and the second electrical measurements within a predefined time window. The system can associate a load supplied through the second utility meter with the transformer in a computer model of the electrical power distribution network.
G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
G06Q 10/0631 - Planification, affectation, distribution ou ordonnancement de ressources d’entreprises ou d’organisations
A system for transferring heat between fluid and a bulk solid. The system includes a plurality of heat exchanger units, each heat exchanger unit comprising: an annular structure including an inner shell and an outer shell; and a first plate and a second plate defining therebetween a conduit for transporting the fluid, wherein the conduit forms a spiral around the inner shell, the spiral extending from the inner shell towards the outer shell, a space between turns of the spiral defining a channel for passage of the bulk solid. The inner shell defines a cylindrical annulus of the annular structure, an axis of the cylindrical annulus being aligned with the direction of gravity during operation. The bulk solid comprises a sorbent material configured to adsorb carbon dioxide from air. The fluid comprises a cooling fluid or a heating fluid.
F28D 7/04 - Appareils échangeurs de chaleur comportant des ensembles de canalisations tubulaires fixes pour les deux sources de potentiel calorifique, ces sources étant en contact chacune avec un côté de la paroi d'une canalisation les canalisations étant enroulées en spirale
71.
Distributed Acoustic Sensing Based on Two-Dimensional Waveguides
The present disclosure generally relates to systems, software, and computer-implemented methods for distributed acoustic sensing (DAS). One example system includes a two-dimensional (2D) waveguide, including a 2D substrate and a waveguide embedded in the 2D substrate, the waveguide configured to backscatter optical signals, and a first optical sensing system. The first optical sensing system can be configured to transmit a first optical signal into the 2D waveguide, receive a backscattered optical signal generated based on backscattering the first optical signal by the 2D waveguide, and generate a sensing result based on the backscattered optical signal.
G01H 9/00 - Mesure des vibrations mécaniques ou des ondes ultrasonores, sonores ou infrasonores en utilisant des moyens sensibles aux radiations, p. ex. des moyens optiques
G01D 5/353 - Moyens mécaniques pour le transfert de la grandeur de sortie d'un organe sensibleMoyens pour convertir la grandeur de sortie d'un organe sensible en une autre variable, lorsque la forme ou la nature de l'organe sensible n'imposent pas un moyen de conversion déterminéTransducteurs non spécialement adaptés à une variable particulière utilisant des moyens optiques, c.-à-d. utilisant de la lumière infrarouge, visible ou ultraviolette avec atténuation ou obturation complète ou partielle des rayons lumineux les rayons lumineux étant détectés par des cellules photo-électriques en modifiant les caractéristiques de transmission d'une fibre optique
G02B 6/125 - Courbures, branchements ou intersections
G02B 6/13 - Circuits optiques intégrés caractérisés par le procédé de fabrication
72.
IIMAGE TRANSLATION FOR IMAGE RECOGNITION TO COMPENSATE FOR SOURCE IMAGE REGIONAL DIFFERENCES
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting locations of utility assets. One of the methods includes receiving an input image of an area in a first geographical region; generating, from the input image and using a generative adversarial network, a corresponding reference image; and generating, by an object detection model and from the reference image, an output that identifies respective locations of one or more utility assets with reference to the input image.
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
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
This disclosure describes a system, method, and computer storage medium for joint asset and defect detection. The approach includes receiving input data including an input image of a utility asset, the input image including one or more objects. Deep neural networks are configured to generate embeddings for classification labels of the one or more objects, each embedding corresponding to a classification label and including a mapping between the classification label and a subset of feature vectors. Defect classifiers are configured to determine a likelihood of an object from the one or more objects in the input image containing a type of defect. Each defect classifier is trained to determine a type of defect based on the embeddings for the one or more classification labels. The approach includes generating an output image that includes bounding boxes for the objects and an annotation corresponding a respective object from the objects.
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
G06V 10/26 - Segmentation de formes dans le champ d’imageDécoupage ou fusion d’éléments d’image visant à établir la région de motif, p. ex. techniques de regroupementDétection d’occlusion
G06V 10/77 - Traitement 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
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
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for characterizing a particulate ingredient of a mixture including a hopper configured to dispense particles along an axis and in freefall through an imaging region, an illumination sub-system including at least one light source arranged at a first location with respect to the axis and configured to illuminate the imaging region, an image capture sub-system including at least one image capture device including a telecentric lens and arranged at a second location with respect to the axis and configured to align a focal plane of the at least one image capture device with the axis within the imaging region, such that when a particle freefalls through the imaging region, the particle is illuminated by the illumination sub-system and the image capture sub-system captures images of at least three silhouettes of the particle within the imaging region.
G06T 7/593 - Récupération de la profondeur ou de la forme à partir de plusieurs images à partir d’images stéréo
G01N 15/00 - Recherche de caractéristiques de particulesRecherche de la perméabilité, du volume des pores ou de l'aire superficielle effective de matériaux poreux
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating actions for a supply chain network. One of the methods includes receiving a request to generate an action in a supply chain network for a particular product based on current state information; providing a request to an action model to generate a respective probability distribution for one or more actions for one or more products; receiving, from the action model, the respective probability distributions for the one or more products; determining, for each product, a binned action from the respective probability distribution; providing a request to a sequence model to generate a respective correction for the one or more binned actions; and receiving, from the sequence model, the respective correction for the respective binned action.
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating actions for a supply chain network. One of the methods includes receiving a request to generate an action in a supply chain network for a particular product based on current state information; providing a request to an action model to generate a respective probability distribution for one or more actions for one or more products; receiving, from the action model, the respective probability distributions for the one or more products; determining, for each product, a binned action from the respective probability distribution; providing a request to a sequence model to generate a respective correction for the one or more binned actions; and receiving, from the sequence model, the respective correction for the respective binned action.
The technology relates to a wireless system (100,200) that can be used indoors or outdoors, and is configured to reduce interference of beacon signals on channels used by the system (100,200). Aspects of the technology provide for evaluation of channel activity to determine an optimal transmission channel. This is beneficial where there is a high density of tags (102,104,400,500,600) that may be configured for data transmission. Tags (102, 104, 400, 500, 600) may include an antenna (440, 540, 6440) to receive signals; a first conditioning element (442,542,642) to attenuate received signals corresponding with the system channels; a converter (444,544,644) and a second conditioning element (446,546,646) to prepare attenuated signals for analysis; a comparator (448,548,648) to compare an attenuated signal to a threshold value; and a processor (450,550,650) to transmit a beacon signal to a reader apparatus (106) based on the comparison.
G06K 7/10 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation électromagnétique, p. ex. lecture optiqueMéthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire
G06K 19/07 - Supports d'enregistrement avec des marques conductrices, des circuits imprimés ou des éléments de circuit à semi-conducteurs, p. ex. cartes d'identité ou cartes de crédit avec des puces à circuit intégré
H04W 4/029 - Services de gestion ou de suivi basés sur la localisation
78.
POLARIZATION BEAM SPLITTER USING ASYMMETRIC POWER SPLITTING AND MULTIPATH INTERFEROMETRY
A polarization beam splitter includes an input port, first and second output ports, and a polarization splitting region coupled between the input port and the first and second output ports. The input port is adapted to receive guided optical signals that are polarization multiplexed, including a transverse electric (TE) optical signal and a transverse magnetic (TM) optical signal. The polarization splitting region includes a pattern of at least two materials having different refractive indexes. The pattern is shaped to demultiplex the TE and TM optical signals by directing a first power majority of the TE optical signal received at the input port to the second output port via asymmetrical power splitting while directing a second power majority of the TM optical signal received at the input port to the first output port via multipath interferometry.
G02B 6/126 - Guides de lumièreDétails de structure de dispositions comprenant des guides de lumière et d'autres éléments optiques, p. ex. des moyens de couplage du type guide d'ondes optiques du genre à circuit intégré utilisant des effets de polarisation
G02B 27/28 - Systèmes ou appareils optiques non prévus dans aucun des groupes , pour polariser
G02B 6/12 - Guides de lumièreDétails de structure de dispositions comprenant des guides de lumière et d'autres éléments optiques, p. ex. des moyens de couplage du type guide d'ondes optiques du genre à circuit intégré
79.
TECHNIQUES FOR USING INVERSE DESIGN FOR COMBINED OPTIMIZATION OF OPTICAL AND ELECTRICAL COMPONENTS IN AN OPTOELECTRONIC RECEIVER
In some embodiments, a computer-implemented method of creating a design for an optoelectronic detector device is provided. A computing system determines an initial design that includes circuit parameters for at least one photodetector region and for conductors that couple the photodetector region to circuitry. The computing system simulates performance of an optically active region to generate a plurality of field values, and simulates performance of the at least one photodetector region based on the plurality of field values to generate charge values. The computing system simulates performance of at least the conductors based on the charge values to generate a performance loss value, and determines a loss metric based on the performance loss value. The computing system backpropagates the loss metric to determine a circuit parameter gradient, and revises the circuit parameters based at least in part on the circuit parameter gradient to create an updated initial design
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
G06F 30/23 - Optimisation, vérification ou simulation de l’objet conçu utilisant les méthodes des éléments finis [MEF] ou les méthodes à différences finies [MDF]
G06N 3/084 - Rétropropagation, p. ex. suivant l’algorithme du gradient
G06F 119/02 - Analyse de fiabilité ou optimisation de fiabilitéAnalyse de défaillance, p. ex. performance dans le pire scénario, analyse du mode de défaillance et de ses effets [FMEA]
G06F 119/10 - Analyse du bruit ou optimisation du bruit
80.
Large Language Models for Predictive Modeling and Inverse Design
An inverse design system combines a large language model (LLM) with a task-specific optimizer, which includes a search function, a forward model, and a comparator. The LLM adjusts parameters of the optimizer's components in response to a design scenario. Then the optimizer processes the design scenario to produce design candidates. Optionally, the LLM learns from the design candidates in an iterative process. A stochastic predictive modeling system combines an LLM with input distributions and a forward model. The LLM adjusts one or more of the input distributions and/or the forward model in response to a forecast scenario. Then the forward model processes a sampling of the input distributions to produce a forward distribution. Optionally, the LLM informs the sampling process. Optionally, the LLM learns from the forward distribution.
Methods, systems, and apparatus for receiving a request for a damage propensity score for a parcel, receiving imaging data for the parcel, wherein the imaging data comprises street-view imaging data of the parcel, extracting, by a machine-learned model including multiple classifiers, characteristics of vulnerability features for the parcel from the imaging data, determining, by the machine-learned model and from the characteristics of the vulnerability features, a damage propensity score for the parcel, and providing a representation of the damage propensity score for display.
An inverse design system combines a large language model (LLM) with a task-specific optimizer, which includes a search function, a forward model, and a comparator. The LLM adjusts parameters of the optimizer's components in response to a design scenario. Then the optimizer processes the design scenario to produce design candidates. Optionally, the LLM learns from the design candidates in an iterative process. A stochastic predictive modeling system combines an LLM with input distributions and a forward model. The LLM adjusts one or more of the input distributions and/or the forward model in response to a forecast scenario. Then the forward model processes a sampling of the input distributions to produce a forward distribution. Optionally, the LLM informs the sampling process. Optionally, the LLM learns from the forward distribution.
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
G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
83.
OPTIMIZATION OF HEATERS FOR TUNING PHOTONIC DEVICES
In some embodiments, a computer-implemented method of creating a design for an optoelectronic device is provided. A computing system determines an initial heater design that includes one or more heater parameters. The computing system determines a temperature gradation by simulating performance of the initial heater design in adjusting an environmental temperature to a nominal temperature. The computing system simulates performance of a nominal optimized design of a dispersive region of the optoelectronic device, given the temperature gradation, to determine a temperature-influenced performance loss value. The computing system determines a heater parameter gradient based on the temperature-influenced performance loss value, and revises the heater parameters based at least in part on the heater parameter gradient to create a revised heater design.
G02B 6/12 - Guides de lumièreDétails de structure de dispositions comprenant des guides de lumière et d'autres éléments optiques, p. ex. des moyens de couplage du type guide d'ondes optiques du genre à circuit intégré
G02B 6/287 - Structuration des guides de lumière pour former des éléments optiques par application de chaleur
G02B 27/00 - Systèmes ou appareils optiques non prévus dans aucun des groupes ,
84.
APTAMER DESIGN BY REINFORCEMENT LEARNING BASED FINE-TUNING OF GENERATIVE LANGUAGE MODELS
The present disclosure relates to a closed loop aptamer development system that leverages in vitro experiments and in silico computation and artificial intelligence-based techniques to iteratively improve a process for identifying binders that can bind a molecular target. Particularly, aspects of the present disclosure are directed to obtaining, using an experimental assay, experimental data for a set of aptamers. The experimental data includes multiple pairs of data, each pair of data having: (i) an aptamer sequence for an aptamer from a set of aptamers, and (ii) a measurement for the characteristic of the aptamer with respect to a given target. A reward model is fine-tuned, using the experimental data, to predict a function-approximation metric for the characteristic of each aptamer in the set of aptamers. A decoder model is fine-tuned for generating novel aptamer sequences based on the function-approximation metric generated by the reward model for the novel aptamer sequences.
A polarization beam splitter includes an input port, first and second output ports, and a polarization splitting region coupled between the input port and the first and second output ports. The input port is adapted to receive guided optical signals that are polarization multiplexed, including a transverse electric (TE) optical signal and a transverse magnetic (TM) optical signal. The polarization splitting region includes a pattern of at least two materials having different refractive indexes. The pattern is shaped to demultiplex the TE and TM optical signals by directing a first power majority of the TE optical signal received at the input port to the second output port via asymmetrical power splitting while directing a second power majority of the TM optical signal received at the input port to the first output port via multipath interferometry.
G02F 1/01 - Dispositifs ou dispositions pour la commande de l'intensité, de la couleur, de la phase, de la polarisation ou de la direction de la lumière arrivant d'une source lumineuse indépendante, p. ex. commutation, ouverture de porte ou modulationOptique non linéaire pour la commande de l'intensité, de la phase, de la polarisation ou de la couleur
G02B 27/00 - Systèmes ou appareils optiques non prévus dans aucun des groupes ,
G02F 1/21 - Dispositifs ou dispositions pour la commande de l'intensité, de la couleur, de la phase, de la polarisation ou de la direction de la lumière arrivant d'une source lumineuse indépendante, p. ex. commutation, ouverture de porte ou modulationOptique non linéaire pour la commande de l'intensité, de la phase, de la polarisation ou de la couleur par interférence
86.
TECHNIQUES FOR USING INVERSE DESIGN FOR COMBINED OPTIMIZATION OF OPTICAL AND ELECTRICAL COMPONENTS IN AN OPTOELECTRONIC RECEIVER
In some embodiments, a computer-implemented method of creating a design for an optoelectronic detector device is provided. A computing system determines an initial design that includes circuit parameters for at least one photodetector region and for conductors that couple the photodetector region to circuitry. The computing system simulates performance of an optically active region to generate a plurality of field values, and simulates performance of the at least one photodetector region based on the plurality of field values to generate charge values. The computing system simulates performance of at least the conductors based on the charge values to generate a performance loss value, and determines a loss metric based on the performance loss value. The computing system backpropagates the loss metric to determine a circuit parameter gradient, and revises the circuit parameters based at least in part on the circuit parameter gradient to create an updated initial design.
In some embodiments, a computer-implemented method of creating a design for an optoelectronic device is provided. A computing system determines an initial heater design that includes one or more heater parameters. The computing system determines a temperature gradation by simulating performance of the initial heater design in adjusting an environmental temperature to a nominal temperature. The computing system simulates performance of a nominal optimized design of a dispersive region of the optoelectronic device, given the temperature gradation, to determine a temperature-influenced performance loss value. The computing system determines a heater parameter gradient based on the temperature-influenced performance loss value, and revises the heater parameters based at least in part on the heater parameter gradient to create a revised heater design.
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a temporal range of a fire. In some implementations, a server obtains a date when a fire occurred within a region. The server obtains satellite imagery of the region from before the date when the fire occurred. The server generates a first statistical distribution from the satellite imagery. The server determines a start date of the fire using the first statistical distribution. The server obtains second satellite imagery of the region from before and after the start date. The server selects a second set of imagery from the second satellite imagery from before the start date. The server generates a second statistical distribution from the second set of imagery. The server determines an end date of the fire using the second statistical distribution. The server provides the start date and the end date for output.
G06F 16/587 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des informations géographiques ou spatiales, p. ex. la localisation
89.
UNIFIED PLATFORM FOR PLANNING AND OPERATIONS OF AN ELECTRIC POWER GRID
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for simulation of electrical power grid behaviors. In some instances, a data model associated with an electrical power grid is obtained. The data model stores static data and dynamic data that can be continuously integrated into the data model based on data streams obtained from data sources associated with properties of the electrical power grid. A set of interfaces can be instantiated for querying data based on the data model. The querying is related to data from at least one of a planning analysis modeling domain or an operation analysis modeling domain from the data model related to the electrical power grid. A query associated with a first planning operation in the planning analysis modeling domain is executed. The query defines one or more nodes of the electrical power grid and relates to the planning analysis domain.
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for simulation of electrical power grid behaviors. In some instances, a data model associated with an electrical power grid is obtained. The data model stores static data and dynamic data that can be continuously integrated into the data model based on data streams obtained from data sources associated with properties of the electrical power grid. A set of interfaces can be instantiated for querying data based on the data model. The querying is related to data from at least one of a planning analysis modeling domain or an operation analysis modeling domain from the data model related to the electrical power grid. A query associated with a first planning operation in the planning analysis modeling domain is executed. The query defines one or more nodes of the electrical power grid and relates to the planning analysis domain.
G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
In some embodiments, a computer-implemented method for simulating performance of a physical device is provided. Calculating a current time step of an operational simulation of the physical device includes, for each voxel of a simulated environment, concurrently with loading a set of field values for the voxel for a previous time step from a main memory, determining permittivity values for the voxel using feature parameter values. The computing system calculates a set of field values for the voxel for the current time step based on the set of field values for the voxel for the previous time step and the permittivity values.
Implementations are described herein for automatically generating multimodal geospatial workflows for accomplishing geospatial tasks. In various implementations, a natural language request may be processed based on generative model(s) such as LLM(s) to generate workflow output tokens that identify high-level actions for completing a geospatial task conveyed in the natural language request. First data indicative of the high-level actions may be processed using one or more of the generative models to generate dataset output tokens that identify responsive dataset(s) that likely contain data responsive to the geospatial task. Second data indicative of both the high-level actions and the responsive dataset(s) may be processed based on one or more of the generative models to generate data manipulation output tokens that identify data manipulation instructions for assembling data from the responsive dataset(s) into a response that fulfills the geospatial task.
G06F 16/387 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des informations géographiques ou spatiales, p. ex. la localisation
G06F 40/284 - Analyse lexicale, p. ex. segmentation en unités ou cooccurrence
93.
FAST ONE-SHOT OPEN VOCABULARY IMAGE-CONDITIONED DETECTION AND SEARCH METHOD FOR UTILITY ASSETS
This disclosure describes a system, method, and non-transitory computer-readable medium for image search-based object detection of utility assets in image databases. The method includes receiving an input image of a utility asset and a query bounding box representing an image-based object query. Bounding boxes of objects represented in the input image are generated based on the input image and the query bounding box, in which anchoring boxes corresponding to object classifications are identified from the bounding boxes. A textual label is determined for a selected subset of anchoring boxes. An image embedding representing the region is encoded, and image tokens are generated based on the encoded image embedding. Output images of other utility assets relevant to the image-based object query are identified from images in an image database, based on at least one of (i) the encoded image embedding, (ii) the image tokens, or (iii) the textual label. The output images are provided for output.
G06F 16/58 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
G06F 16/535 - Filtrage basé sur des données supplémentaires, p. ex. sur des profils d'utilisateurs ou de groupes
Implementations are described herein for automatically generating multimodal geospatial workflows for accomplishing geospatial tasks. In various implementations, a natural language request may be processed based on generative model(s) such as LLM(s) to generate workflow output tokens that identify high-level actions for completing a geospatial task conveyed in the natural language request. First data indicative of the high-level actions may be processed using one or more of the generative models to generate dataset output tokens that identify responsive dataset(s) that likely contain data responsive to the geospatial task. Second data indicative of both the high-level actions and the responsive dataset(s) may be processed based on one or more of the generative models to generate data manipulation output tokens that identify data manipulation instructions for assembling data from the responsive dataset(s) into a response that fulfills the geospatial task.
G06F 16/909 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des informations géographiques ou spatiales, p. ex. la localisation
95.
AGGREGATING DISPARATE DATA REPRESENTATIVE OF AN ADVERSE EVENT FOR MACHINE LEARNING
Methods, systems, and apparatus for accepting, by a training system, a plurality of sets of data elements, wherein a first set of data elements describe a first property of a first adverse event, a second set of data elements describe the first property of a second adverse event, and a third set of data elements describe the first property of a third adverse event, determining, by the training system, that the first adverse event and the second adverse event are associated with a first adverse event complex, and in response: aggregating at least a subset of the first set of data elements and at least a subset of the second set of data elements into an aggregate set of data elements describing the first property for the first adverse event complex, and training, by the training system, a ML model.
G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Scientific research and development; research and
development of technology in the fields of biology,
synthetic biology, pharmaceutical preparations,
biotechnology, living systems, renewable materials,
chemicals, organisms, and bioprocesses; research,
development and engineering services in the fields of
biology, synthetic biology, pharmaceutical preparations,
biotechnology, living systems, renewable materials,
chemicals, organisms, and bioprocesses; design, engineering,
research, development and testing services in the fields of
biology, synthetic biology, pharmaceutical preparations,
biotechnology, living systems, renewable materials,
chemicals, organisms, and bioprocesses; custom synthesis in
the nature of genetic engineering of DNA, biological
organisms, cells, viruses and special purpose cells for
scientific, engineering, research, medical, agricultural,
food, chemical, energy, industrial, and manufacturing use;
consulting services in the fields of research in biology,
synthetic biology, pharmaceutical preparations,
biotechnology, living systems, renewable materials,
chemicals, organisms, and bioprocesses; biotechnology
research; biological research; design of computer-simulated
models; computer modeling services in the fields of biology,
synthetic biology, pharmaceutical preparations,
biotechnology, living systems, renewable materials,
chemicals, organisms, and bioprocesses; providing online
non-downloadable proprietary software to evaluate, analyze
and collect data for data automation and collection purposes
in the fields of scientific research and engineering;
providing temporary use of on-line non-downloadable software
development tools using artificial intelligence (AI),
machine learning, and deep learning for research, modeling,
data collection, data ingestion, data storage, and
simulations in the fields of biology, synthetic biology,
pharmaceutical preparations, biotechnology, living systems,
renewable materials, chemicals, organisms, and bioprocesses;
computer software platforms using artificial intelligence
(AI), machine learning, and deep learning for research,
modeling, data collection, data ingestion, data storage, and
simulations in the fields of biology, synthetic biology,
pharmaceutical preparations, biotechnology, living systems,
renewable materials, chemicals, organisms, and bioprocesses.
Techniques for providing carbon dioxide include generating thermal energy, an exhaust fluid, and electrical power from a power plant; providing the exhaust fluid and the generated electrical power to an exhaust fluid scrubbing system to separate components of the exhaust fluid; capturing heat from a source of heat of an industrial process in a heating fluid; transferring the heat of the industrial process captured in the heating fluid to a carbon dioxide source material of a direct air capture (DAC) system; providing the generated electrical power from the power plant to the DAC system; providing the thermal energy from the power plant to the DAC system; and separating, with the transferred portion of the heat of the industrial process and the provided thermal energy, carbon dioxide from the carbon dioxide source material of the DAC system.
F25J 3/02 - Procédés ou appareils pour séparer les constituants des mélanges gazeux impliquant l'emploi d'une liquéfaction ou d'une solidification par rectification, c.-à-d. par échange continuel de chaleur et de matière entre un courant de vapeur et un courant de liquide
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Research and development of new products; Providing a website that features information on product research and product development; Providing information in the fields of technology and product design and development; Providing a website featuring information on the use of technology to solve international problems; Design and testing for new product development; Scientific and technological research and development services; Research and development in the field of computer software and hardware; Research and development in the field of software and technology using artificial intelligence and machine learning; Development of new technology for others in the field of artificial intelligence and machine learning; Development of new technology for others in the field of environmental sustainability, software automation, supply chain logistics, communications and Internet access, utility access and monitoring, and bioengineering
99.
IMAGING A SUBTERRANEAN FORMATION THROUGH ACOUSTIC ENERGY DELIVERED THROUGH A LIQUID
Techniques for imaging a subterranean formation include activating an acoustic energy source that is at least partially submerged in a volume of liquid on or under a terranean surface; based on the activating, producing acoustic wave energy that travels through the volume of liquid and to a subterranean zone below the terranean surface; receiving, at one or more acoustic receivers, reflected acoustic wave energy from the subterranean zone; and generating, with a control system, data associated with the subterranean zone based on the reflected acoustic wave energy.
Methods, systems, and apparatus for an infrared and visible imaging system. In some implementations, Image data from a visible-light camera is obtained. A position of a device is determined based at least in part on the image data from the visible-light camera. An infrared camera is positioned so that the device is in a field of view of the infrared camera, with the field of view of the infrared camera being narrower than the field of view of the visible-light camera. Infrared image data from the infrared camera that includes regions representing the device is obtained. Infrared image data from the infrared camera that represents the device is recorded. Position data is also recorded that indicates the location and pose of the infrared camera when the infrared image data is acquired by the infrared camera.
H04N 23/661 - Transmission des signaux de commande de la caméra par le biais de réseaux, p. ex. la commande via Internet
B60R 11/04 - Montage des caméras pour fonctionner pendant la marcheDisposition de leur commande par rapport au véhicule
G01C 19/56 - Dispositifs sensibles à la rotation utilisant des masses vibrantes, p. ex. capteurs vibratoires de vitesse angulaire basés sur les forces de Coriolis
G01J 5/00 - Pyrométrie des radiations, p. ex. thermométrie infrarouge ou optique
G01J 5/07 - Dispositions pour ajuster l’angle solide des radiations captées, p. ex. ajustement ou orientation du champ de vue, suivi de la position ou encodage de la position angulaire
