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
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
3.
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
4.
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]
5.
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
10.
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
13.
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
15.
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
18.
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
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
25.
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.
27.
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.
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 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
31.
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
32.
2X2 PHOTONIC SPLITTER USING MODE CONVERTING Y-JUNCTIONS
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
33.
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 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
42.
ELECTRICAL GRID SERVICE MONITORING, VALUATION, AND CONTROL
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
44.
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
45.
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
51.
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
52.
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
53.
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"
56.
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 ,
57.
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
59.
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
62.
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.
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 16/387 - 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
67.
GENERATION AND IMPLEMENTATION OF GEOSPATIAL WORKFLOWS
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
68.
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
09 - Appareils et instruments scientifiques et électriques
38 - Services de télécommunications
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Telecommunication exchangers; telecommunication cables; telecommunication transmitters; electric capacitators for telecommunication apparatus; broadband wireless equipment, namely, telecommunications base station equipment for cellular and fixed networking and communications applications; telecommunications hardware and recorded software for monitoring and alerting remote sensor status via the Internet sold as a unit; lasers for non-medical use; laser equipment for non-medical purposes; electronic and optical communications instruments and components, namely, optical transmitters, optical receivers, communication link testers for testing communication links, digital transmitters, optical transceivers, and optical data links; telecommunications equipment, namely, free-space optics transmission systems; downloadable computer software for providing internet and broadband access. Telecommunication services, namely, providing internet access, fiber optic network services, gateway services, routing and junction services, and telecommunication consultation; providing telecommunications connections to the Internet or databases; telecommunication services, namely, providing internet access via free-space optics transmission systems. Computer technology consulting in the fields of information technology relating to computer network design, computer programming, and global communication computer network design; design for others in the fields of information technology, computer programming, telecommunications and global computer networks; installation and maintenance of Internet access software; software as a service (SAAS) services featuring software for providing internet and broadband access.
09 - Appareils et instruments scientifiques et électriques
38 - Services de télécommunications
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Telecommunication exchangers; telecommunication cables; telecommunication transmitters; electric capacitators for telecommunication apparatus; broadband wireless equipment, namely, telecommunications base station equipment for cellular and fixed networking and communications applications; telecommunications hardware and recorded software for monitoring and alerting remote sensor status via the Internet sold as a unit; lasers for non-medical use; laser equipment for non-medical purposes; electronic and optical communications instruments and components, namely, optical transmitters, optical receivers, communication link testers for testing communication links, digital transmitters, optical transceivers, and optical data links; telecommunications equipment, namely, free-space optics transmission systems; downloadable computer software for providing internet and broadband access. Telecommunication services, namely, providing internet access, fiber optic network services, gateway services, routing and junction services, and telecommunication consultation; providing telecommunications connections to the Internet or databases; telecommunication services, namely, providing internet access via free-space optics transmission systems. Computer technology consulting in the fields of information technology relating to computer network design, computer programming, and global communication computer network design; design for others in the fields of information technology, computer programming, telecommunications and global computer networks; installation and maintenance of Internet access software; software as a service (SAAS) services featuring software for providing internet and broadband access.
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 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; New company incubator services; 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 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, automation, supply chain logistics, communications and Internet access, utility access and monitoring, and bioengineering.
74.
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
In some embodiments, a computer-implemented method for designing a physical device is provided. A computing system generates an initial design based on a design specification. The initial design includes a list of features, and each feature of the list of features represents a convex shape. The computing system determines a set of signed distance fields that includes a signed distance field for each feature of the list of features, and determines a set of structural parameters using the set of signed distance fields. The computing system simulates performance of the initial design using the set of structural parameters to determine a performance loss value. The computing system determines at least one fabrication loss value using the set of signed distance fields. The computing system updates at least one feature of the list of features using the at least one fabrication loss value and a gradient of the performance loss value.
Methods, systems, and apparatus for using one or more machine learning (ML) models to mitigate effects of climate change by evaluating impact of wildfire mitigation actions (WMAs) for selective deployment of WMAs.
Disclosed implementations relate to adding "bottleneck" models to machine learning pipelines that already apply domain models to translate and/or transfer representations of high-level semantic concepts between domains. In various implementations, an initial representation in a first domain of a transition from an initial state of an environment to a goal state of the environment may be processed based on a pre-trained first domain encoder to generate a first embedding that semantically represents the transition. The first embedding may be processed based on one or more bottleneck models to generate a second embedding with fewer dimensions than the first embedding. In various implementations, the second embedding may be processed in various ways to train one or more of the bottleneck model(s) based on various different auxiliary loss functions.
Methods, systems, and apparatus, including computer programs encoded on a storage device, for filling gaps in electric grid models are enclosed. A method includes obtaining vector data representing first portions of paths of electric grid wires over a geographic region; converting the vector data to first raster image data that depicts an overhead view of the electric grid wires including a first set of line segments representing the first portions of the paths; processing the first raster image data using a gap filling model; obtaining, as output from the gap filling model, second raster image data including a second set of line segments corresponding to gaps included in the input raster image data and representing second portions of paths of the electric grid wires; and converting the second raster image data to vector data representing the first portions and the second portions of paths of the electric grid wires.
G06T 11/20 - Traçage à partir d'éléments de base, p. ex. de lignes ou de cercles
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 a storage device, for mapping an electrical grid are disclosed. A method includes sampling multiple locations within a geographic region, executing a detection process for each location, the detection process including applying the set of images for the location as input to a machine learning (ML) model that is trained to identify electrical grid assets depicted within images taken from a combination of different perspectives and obtaining an output from the machine learning model that indicates whether a same electrical grid asset is identified in each of the images of the location. In response to an ML output that indicates a positive identification of the same electrical grid asset being depicted in a particular set of images of a particular location, the method further includes: selecting a number of sublocations within the region, and executing the detection process for each sublocation.
G06T 7/70 - Détermination de la position ou de l'orientation des objets ou des caméras
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”
81.
REDUCING GREENHOUSE GASES THROUGH EVALUATION AND DEPLOYMENT OF WILDFIRE MITIGATION ACTIONS USING MACHINE LEARNING
Methods, systems, and apparatus for using one or more machine learning (ML) models to mitigate effects of climate change by evaluating impact of wildfire mitigation actions (WMAs) for selective deployment of WMAs.
Methods, systems, and apparatus, including computer programs encoded on a storage device, for mapping an electrical grid are disclosed. A method includes sampling multiple locations within a geographic region, executing a detection process for each location, the detection process including applying the set of images for the location as input to a machine learning (ML) model that is trained to identify electrical grid assets depicted within images taken from a combination of different perspectives and obtaining an output from the machine learning model that indicates whether a same electrical grid asset is identified in each of the images of the location. In response to an ML output that indicates a positive identification of the same electrical grid asset being depicted in a particular set of images of a particular location, the method further includes: selecting a number of sublocations within the region, and executing the detection process for each sublocation.
G06F 18/214 - Génération de motifs d'entraînementProcédés de Bootstrapping, p. ex. ”bagging” ou ”boosting”
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”
Disclosed implementations relate to adding “bottleneck” models to machine learning pipelines that already apply domain models to translate and/or transfer representations of high-level semantic concepts between domains. In various implementations, an initial representation in a first domain of a transition from an initial state of an environment to a goal state of the environment may be processed based on a pre-trained first domain encoder to generate a first embedding that semantically represents the transition. The first embedding may be processed based on one or more bottleneck models to generate a second embedding with fewer dimensions than the first embedding. In various implementations, the second embedding may be processed in various ways to train one or more of the bottleneck model(s) based on various different auxiliary loss functions.
A method includes generating a greenhouse gas (GHG) mitigation credit including identifying a set of tasks to be completed by a respective set of first entities that collectively generate a GHG mitigation having a set of GHG mitigation parameters; receiving, from a second entity, a request for a GHG credit acquisition for the GHG mitigation credit; in response to receiving the request, executing the request for the GHG credit acquisition and providing the GHG mitigation credit to the second entity; and providing, to at least one of the set of first entities, instructions to cause the at least one of the set of first entities to execute a respective task of the set of tasks.
G06Q 10/0637 - Gestion ou analyse stratégiques, p. ex. définition d’un objectif ou d’une cible pour une organisationPlanification des actions en fonction des objectifsAnalyse ou évaluation de l’efficacité des objectifs
A method includes: generating a set of tasks; determining, by a machine learning model and based on multiple data types from multiple sources, that an overall risk score exceeds a first failure threshold due to a risk score of a task exceeding a second threshold; selecting a replacement task for the task, the selecting including: receiving, replacement candidates, each replacement candidate including a candidate offset potential and one or more candidate failure mechanisms; assigning, by the machine learning model and to each of the replacement candidates, a replacement score for the replacement candidate based on a failure correlation of the replacement candidate with respect to each other sets of the set of tasks; ranking the replacement candidates based on the replacement scores; and selecting, based on the ranking, the replacement task; and generating, an updated set of tasks including the replacement task.
Aspects of the disclosure provide a method of converting power received in one or more optical power beams to electrical power. The method comprising receiving, at an OP A (114, 418, 504) of a first optical terminal (102, 402), a first optical power beam from a remote optical terminal (122, 412); determining, by one or more processors (104, 424, 516, 516b, 516c, 516e), a first distribution of the received first optical power beam across a plurality of cells (510), wherein the plurality of cells (510) are configured to convert power from the from optical power beams to electrical power, and the first distribution is determined based on an initial conversion capability of each of the plurality of cells (510); distributing, by an optical switch matrix (508), power from the first optical power beam across the plurality of cells (510) based on the determined first distribution; and converting, by the plurality of cells (510), at least a portion of the first optical power beam to electrical power.
H02J 50/30 - Circuits ou systèmes pour l'alimentation ou la distribution sans fil d'énergie électrique utilisant de la lumière, p. ex. des lasers
H02J 50/40 - Circuits ou systèmes pour l'alimentation ou la distribution sans fil d'énergie électrique utilisant plusieurs dispositifs de transmission ou de réception
H04B 10/80 - Aspects optiques concernant l’utilisation de la transmission optique pour des applications spécifiques non prévues dans les groupes , p. ex. alimentation par faisceau optique ou transmission optique dans l’eau
A method includes: generating a set of tasks; determining, by a machine learning model and based on multiple data types from multiple sources, that an overall risk score exceeds a first failure threshold due to a risk score of a task exceeding a second threshold; selecting a replacement task for the task, the selecting including: receiving, replacement candidates, each replacement candidate including a candidate offset potential and one or more candidate failure mechanisms; assigning, by the machine learning model and to each of the replacement candidates, a replacement score for the replacement candidate based on a failure correlation of the replacement candidate with respect to each other sets of the set of tasks; ranking the replacement candidates based on the replacement scores; and selecting, based on the ranking, the replacement task; and generating, an updated set of tasks including the replacement task.
G06Q 10/0631 - Planification, affectation, distribution ou ordonnancement de ressources d’entreprises ou d’organisations
G06Q 10/0635 - Analyse des risques liés aux activités d’entreprises ou d’organisations
G06Q 10/0637 - Gestion ou analyse stratégiques, p. ex. définition d’un objectif ou d’une cible pour une organisationPlanification des actions en fonction des objectifsAnalyse ou évaluation de l’efficacité des objectifs
A method includes: generating a greenhouse gas (GHG) mitigation credit including identifying a set of tasks to be completed by a respective set of first entities that collectively generate a GHG mitigation having a set of GHG mitigation parameters; receiving, from a second entity, a request for a GHG credit acquisition for the GHG mitigation credit; in response to receiving the request, executing the request for the GHG credit acquisition and providing the GHG mitigation credit to the second entity; and providing, to at least one of the set of first entities, instructions to cause the at least one of the set of first entities to execute a respective task of the set of tasks.
G01N 33/00 - Recherche ou analyse des matériaux par des méthodes spécifiques non couvertes par les groupes
G06Q 10/0635 - Analyse des risques liés aux activités d’entreprises ou d’organisations
G06Q 10/0637 - Gestion ou analyse stratégiques, p. ex. définition d’un objectif ou d’une cible pour une organisationPlanification des actions en fonction des objectifsAnalyse ou évaluation de l’efficacité des objectifs
G06Q 30/018 - Certification d’entreprises ou de produits
G06Q 30/0214 - Systèmes de récompense de recommandation
G06Q 40/04 - TransactionsOpérations boursières, p. ex. actions, marchandises, produits dérivés ou change de devises
89.
OPTIMIZING ENERGY EFFICIENCY FOR ORE SMELTING IN BLAST FURNACES BY SURFACE SCANNING
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for optimizing energy efficiency for ore smelting in blast furnaces. One of the methods is a pelletization process control method that includes obtaining images of pelletized particles; determining one or more characteristics of the pelletized particles; in response to determining that at least one or more of the characteristics is outside of a pelletization parameter, determining an adjustment to a control parameter of the pelletization system; and sending one or more signals to adjust the control parameter of the pelletization system. Another method is an iron ore smelting method that includes determining quantities of reactants to be added to the blast furnace with the pelletized particles in the stream of pelletized particles; and sending one or more signals that cause the controller to add the reactants of to the blast furnace according to the determined quantities.
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for selecting, from a set of actions, actions to be performed by an agent interacting with an environment to cause the agent to perform a task. One of the methods includes receiving a current observation characterizing a current environment state of the environment, selecting an action to be performed by the agent in response to the current observation by performing multiple iterations of outer look ahead search, wherein performing the multiple iterations of outer look ahead search comprises, in each outer look ahead search iteration: determining a proper subset of the possible future states of the environment; determining that one or more inner look ahead search commencement criteria are satisfied; and in response, performing an inner look ahead search of the proper subset of the possible future states of the environment.
Provided herein are methods of reducing the chemical content such as metal, sulfur, phosphorus, and/or organic content of waste. The methods and systems include contacting waste with an acid or base to neutralize the waste.
C02F 1/461 - Traitement de l'eau, des eaux résiduaires ou des eaux d'égout par des procédés électrochimiques par électrolyse
C02F 1/469 - Traitement de l'eau, des eaux résiduaires ou des eaux d'égout par des procédés électrochimiques par séparation électrochimique, p. ex. par électro-osmose, électrodialyse, électrophorèse
C02F 1/66 - Traitement de l'eau, des eaux résiduaires ou des eaux d'égout par neutralisationAjustage du pH
C02F 101/22 - Chrome ou composés du chrome, p. ex. chromates
C02F 101/34 - Composés organiques contenant de l'oxygène
C02F 103/08 - Eau de mer, p. ex. pour le dessalement
C02F 103/10 - Nature de l'eau, des eaux résiduaires ou des eaux ou boues d'égout à traiter provenant de carrières ou d'activités minières
C02F 103/16 - Nature de l'eau, des eaux résiduaires ou des eaux ou boues d'égout à traiter provenant de procédés métallurgiques, c.-à-d. de la production, de la purification ou du traitement de métaux, p. ex. déchets de procédés électrolytiques
C02F 103/18 - Nature de l'eau, des eaux résiduaires ou des eaux ou boues d'égout à traiter provenant de l'épuration des effluents gazeux par voie humide
92.
MULTI-MODAL ARTIFICIAL INTELLIGENCE PLATFORM FOR BUILDING CONSTRUCTION
Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for a multi-modal artificial intelligence platform for building construction. The multi-model artificial intelligence platform includes various engines that perform various computer-implemented methods. The various engines include a site selector artificial intelligence (AI) engine, a geospatial database, a site compliance analyzer AI engine, a masterplan generator AI engine, a compliance analyzer AI engine, an aesthetic generator AI engine, a schematic generator AI engine, a construction plan generator AI engine, a project timeline generator AI engine, a compliance application generator AI engine, and a financial model generator AI engine. Respective AI engines collaboratively cooperate for end-to-end AI-driven building construction design and development.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
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
An inverter coupled to an electrical power grid characterizes the electrical power grid. The inverter outputs a plurality of electrical signals of different frequencies to the electrical power grid, measures responses of the electrical power grid to the plurality of electrical signals to obtain measurement data, and processes the measurement data to generate prediction data that characterizes one or more fault conditions of the electrical power grid. The inverter adjusts an operational setting of the inverter based on the prediction data. The operational setting affects a response of the electrical power grid to a fault condition.
C04B 20/00 - Emploi de matières comme charges pour mortiers, béton ou pierre artificielle prévu dans plus d'un groupe et caractérisées par la forme ou la répartition des grainsTraitement de matières spécialement adapté pour renforcer leur propriétés de charge dans les mortiers, béton ou pierre artificielle prévu dans plus d'un groupe de Matières expansées ou défibrillées
C04B 40/00 - Procédés, en général, pour influencer ou modifier les propriétés des compositions pour mortiers, béton ou pierre artificielle, p. ex. leur aptitude à prendre ou à durcir
G01N 15/0205 - Recherche de la dimension ou de la distribution des dimensions des particules par des moyens optiques
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
96.
CHARACTERIZING ELECTRICAL GRID AND PREDICTING FAULT CONDITIONS USING INVERTERS
An inverter coupled to an electrical power grid characterizes the electrical power grid. The inverter outputs a plurality of electrical signals of different frequencies to the electrical power grid, measures responses of the electrical power grid to the plurality of electrical signals to obtain measurement data, and processes the measurement data to generate prediction data that characterizes one or more fault conditions of the electrical power grid. The inverter adjusts an operational setting of the inverter based on the prediction data. The operational setting affects a response of the electrical power grid to a fault condition.
09 - Appareils et instruments scientifiques et électriques
40 - Traitement de matériaux; recyclage, purification de l'air et traitement de l'eau
42 - Services scientifiques, technologiques et industriels, recherche et conception
45 - Services juridiques; services de sécurité; services personnels pour individus
Produits et services
Photonic integrated circuits; semiconductor devices;
photonic components and systems for use in optical
communication networks, namely, optical transceivers; indium
phosphide-based photonic components, namely, integrated
circuits; optical circuits, namely, integrated circuits;
downloadable and recorded operating software for use in
photonic integrated circuits, semiconductors, integrated
circuits, fiber optic hardware, electro-optic components,
optical transceivers and receivers; downloadable and
recorded software for electromagnetic design, modeling and
simulation, of integrated optics and photonic components;
fiber optic hardware; electro-optic components; optical
transceivers and receivers; metasurface optics; quantum
computers; telecommunications hardware; computer chipsets;
downloadable and recorded computer software for
communication, wireless communication and connectivity;
downloadable and recorded firmware for using and controlling
wireless broadband communication technology and to enable
communication and wireless communication; microprocessors;
microprocessor cores; central processing units; converged
network interface controllers; integrated circuits;
downloadable and recorded software for communication,
interoperability and connectivity, and for controlling and
using integrated circuits; software contained or embedded in
computer hardware for communication, interoperability and
connectivity, and for controlling and using integrated
circuits. Consulting services in the field of manufacturing process
for photonic integrated circuits, semiconductors, integrated
circuits, fiber optic hardware, electro-optic components,
optical transceivers and receivers. Design, development, and engineering of photonic integrated
circuits, semiconductors, integrated circuits, fiber optic
hardware, electro-optic components, optical transceivers and
receivers, antennas, radio-frequency receivers and
transmitters; research and engineering services in the field
of photonics, integrated photonics design, electronics
design, and fiber-optic technology; consulting in the fields
of design, development, engineering, and electronic
monitoring of photonic integrated circuits, semiconductors,
integrated circuits, fiber optic hardware, electro-optic
components, optical transceivers and receivers, antennas,
radio-frequency receivers and transmitters; technical
support services, namely, troubleshooting in the nature of
diagnosing computer hardware and software problems and
monitoring technological functions being product testing of
photonic integrated circuits, semiconductors, integrated
circuits, fiber optic hardware, electro-optic components,
optical transceivers and receivers, antennas,
radio-frequency receivers and transmitters; engineering
services; product research and development; development of
software for photonic integrated circuits, semiconductors,
integrated circuits, fiber optic hardware, electro-optic
components, optical transceivers and receivers, antennas,
radio-frequency receivers and transmitters; quantum
computing. Licensing of intellectual property.
Methods, systems, and apparatus, including medium-encoded computer program products, for an access controlled power grid model. A power grid model can include multiple regions. Access can be provided only to a subset of regions based on access privileges, and the user can be denied access to regions of the power grid model outside of the subset. A simulation can be executed using input from the user and can include simulation parameters for at least one of the regions in the subset. The simulation can be executed on the regions of the power grid model in the subset and at least one additional region that is not in the subset. The simulation can produce results that can include electrical values of components in the regions within the subset and values of components in at least one additional region. The output can include only the simulation results for regions within the subset.
This disclosure describes a system and method for enabling an inverter to temporarily sustain fault current. One implementation is a system that includes an inverter having a plurality of transistors. A reservoir having an outlet channel is configured to contain a compressed gas. The outlet channel is arranged to direct the compressed gas towards a heatsink in thermal communication with one or more of the plurality of transistors. A control valve can be positioned between the reservoir and the outlet channel and a controller can be configured to detect an overcurrent event in the inverter and, in response, open the control valve. A transformer is electrically connected to an output of the inverter and configured to step down voltage from the inverter to a circuit being supplied by the inverter.
In some embodiments, a method for creating a design for a physical device is provided. A computing system receives a design specification. The computing system generates a proposed design based on the design specification. The computing system determines a vector of loss values based on the proposed design. The computing system determines a scalar loss value based on a distance between the vector of loss values and a volume representing desired characteristics of the physical device. The computing system updates the proposed design based on the scalar loss value.
G06F 111/06 - Optimisation multi-objectif, p. ex. optimisation de Pareto utilisant le recuit simulé, les algorithmes de colonies de fourmis ou les algorithmes génétiques
