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 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
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 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G06F 16/58 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
G06F 16/587 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using geographical or spatial information, e.g. location
5.
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 - Design verification, e.g. using simulation, simulation program with integrated circuit emphasis [SPICE], direct methods or relaxation methods
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.
7.
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 103/12 - Nature of the water, waste water, sewage or sludge to be treated from the silicate or ceramic industries, e.g. waste waters from cement or glass factories
C04B 18/00 - Use of agglomerated or waste materials or refuse as fillers for mortars, concrete or artificial stoneTreatment of agglomerated or waste materials or refuse, specially adapted to enhance their filling properties in mortars, concrete or artificial stone
8.
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.
G16B 40/00 - ICT specially adapted for biostatisticsICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
G16B 30/00 - ICT specially adapted for sequence analysis involving nucleotides or amino acids
9.
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 - Optical coupling means having data bus means, i.e. plural waveguides interconnected and providing an inherently bidirectional system by mixing and splitting signals
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 - Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
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 - Optical coupling means having data bus means, i.e. plural waveguides interconnected and providing an inherently bidirectional system by mixing and splitting signals
G02B 6/293 - Optical coupling means having data bus means, i.e. plural waveguides interconnected and providing an inherently bidirectional system by mixing and splitting signals with wavelength selective means
13.
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 - Solid sorbent compositions or filter aid compositionsSorbents for chromatographyProcesses for preparing, regenerating or reactivating thereof characterised by their form or physical properties
B01D 53/04 - Separation of gases or vapoursRecovering vapours of volatile solvents from gasesChemical or biological purification of waste gases, e.g. engine exhaust gases, smoke, fumes, flue gases or aerosols by adsorption, e.g. preparative gas chromatography with stationary adsorbents
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.
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.
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 - Solid sorbent compositions or filter aid compositionsSorbents for chromatographyProcesses for preparing, regenerating or reactivating thereof characterised by their form or physical properties
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 - Processes for preparing, regenerating or reactivating
B01J 20/10 - Solid sorbent compositions or filter aid compositionsSorbents for chromatographyProcesses for preparing, regenerating or reactivating thereof comprising inorganic material comprising silica or silicate
B01J 20/28 - Solid sorbent compositions or filter aid compositionsSorbents for chromatographyProcesses for preparing, regenerating or reactivating thereof characterised by their form or physical properties
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 - Separation of gases or vapoursRecovering vapours of volatile solvents from gasesChemical or biological purification of waste gases, e.g. engine exhaust gases, smoke, fumes, flue gases or aerosols by adsorption, e.g. preparative gas chromatography with stationary adsorbents
B01J 20/28 - Solid sorbent compositions or filter aid compositionsSorbents for chromatographyProcesses for preparing, regenerating or reactivating thereof characterised by their form or physical properties
B01J 20/30 - Processes for preparing, regenerating or reactivating
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 - Heat-exchange apparatus having stationary plate-like or laminated conduit assemblies for both heat-exchange media, the media being in contact with different sides of a conduit wall the conduits being formed by spirally-wound plates or laminae
F28D 7/04 - Heat-exchange apparatus having stationary tubular conduit assemblies for both heat-exchange media, the media being in contact with different sides of a conduit wall the conduits being spirally coiled
F25B 15/16 - Sorption machines, plants or systems, operating continuously, e.g. absorption type using desorption cycle
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 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G06Q 10/0631 - Resource planning, allocation, distributing or scheduling for enterprises or organisations
A system for transferring heat between fluid and a bulk solid. The system includes a plurality of heat exchanger units, each heat exchanger unit comprising: an annular structure including an inner shell and an outer shell; and a first plate and a second plate defining therebetween a conduit for transporting the fluid, wherein the conduit forms a spiral around the inner shell, the spiral extending from the inner shell towards the outer shell, a space between turns of the spiral defining a channel for passage of the bulk solid. The inner shell defines a cylindrical annulus of the annular structure, an axis of the cylindrical annulus being aligned with the direction of gravity during operation. The bulk solid comprises a sorbent material configured to adsorb carbon dioxide from air. The fluid comprises a cooling fluid or a heating fluid.
F28D 7/04 - Heat-exchange apparatus having stationary tubular conduit assemblies for both heat-exchange media, the media being in contact with different sides of a conduit wall the conduits being spirally coiled
24.
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 - Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves by using radiation-sensitive means, e.g. optical means
G01D 5/353 - Mechanical means for transferring the output of a sensing memberMeans for converting the output of a sensing member to another variable where the form or nature of the sensing member does not constrain the means for convertingTransducers not specially adapted for a specific variable using optical means, i.e. using infrared, visible or ultraviolet light with attenuation or whole or partial obturation of beams of light the beams of light being detected by photocells influencing the transmission properties of an optical fibre
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 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
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 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
G06V 10/77 - Processing image or video features in feature spacesArrangements for image or video recognition or understanding using pattern recognition or machine learning using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]Blind source separation
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
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.
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 - Methods or arrangements for sensing record carriers by electromagnetic radiation, e.g. optical sensingMethods or arrangements for sensing record carriers by corpuscular radiation
G06K 19/07 - Record carriers with conductive marks, printed circuits or semiconductor circuit elements, e.g. credit or identity cards with integrated circuit chips
H04W 4/029 - Location-based management or tracking services
31.
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 - Light guidesStructural details of arrangements comprising light guides and other optical elements, e.g. couplings of the optical waveguide type of the integrated circuit kind using polarisation effects
G02B 27/28 - Optical systems or apparatus not provided for by any of the groups , for polarising
G02B 6/12 - Light guidesStructural details of arrangements comprising light guides and other optical elements, e.g. couplings of the optical waveguide type of the integrated circuit kind
32.
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 - Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
G06F 30/23 - Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
G06N 3/084 - Backpropagation, e.g. using gradient descent
G06F 119/02 - Reliability analysis or reliability optimisationFailure analysis, e.g. worst case scenario performance, failure mode and effects analysis [FMEA]
G06F 119/10 - Noise analysis or noise optimisation
33.
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 - Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
36.
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 - Light guidesStructural details of arrangements comprising light guides and other optical elements, e.g. couplings of the optical waveguide type of the integrated circuit kind
G02B 6/287 - Structuring of light guides to shape optical elements with heat application
G02B 27/00 - Optical systems or apparatus not provided for by any of the groups ,
37.
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 - Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulatingNon-linear optics for the control of the intensity, phase, polarisation or colour
G02B 27/00 - Optical systems or apparatus not provided for by any of the groups ,
G02F 1/21 - Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulatingNon-linear optics for the control of the intensity, phase, polarisation or colour by interference
39.
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 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using geographical or spatial information, e.g. location
42.
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 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
In some embodiments, a computer-implemented method for simulating performance of a physical device is provided. Calculating a current time step of an operational simulation of the physical device includes, for each voxel of a simulated environment, concurrently with loading a set of field values for the voxel for a previous time step from a main memory, determining permittivity values for the voxel using feature parameter values. The computing system calculates a set of field values for the voxel for the current time step based on the set of field values for the voxel for the previous time step and the permittivity values.
Implementations are described herein for automatically generating multimodal geospatial workflows for accomplishing geospatial tasks. In various implementations, a natural language request may be processed based on generative model(s) such as LLM(s) to generate workflow output tokens that identify high-level actions for completing a geospatial task conveyed in the natural language request. First data indicative of the high-level actions may be processed using one or more of the generative models to generate dataset output tokens that identify responsive dataset(s) that likely contain data responsive to the geospatial task. Second data indicative of both the high-level actions and the responsive dataset(s) may be processed based on one or more of the generative models to generate data manipulation output tokens that identify data manipulation instructions for assembling data from the responsive dataset(s) into a response that fulfills the geospatial task.
G06F 16/387 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using geographical or spatial information, e.g. location
G06F 40/284 - Lexical analysis, e.g. tokenisation or collocates
46.
FAST ONE-SHOT OPEN VOCABULARY IMAGE-CONDITIONED DETECTION AND SEARCH METHOD FOR UTILITY ASSETS
This disclosure describes a system, method, and non-transitory computer-readable medium for image search-based object detection of utility assets in image databases. The method includes receiving an input image of a utility asset and a query bounding box representing an image-based object query. Bounding boxes of objects represented in the input image are generated based on the input image and the query bounding box, in which anchoring boxes corresponding to object classifications are identified from the bounding boxes. A textual label is determined for a selected subset of anchoring boxes. An image embedding representing the region is encoded, and image tokens are generated based on the encoded image embedding. Output images of other utility assets relevant to the image-based object query are identified from images in an image database, based on at least one of (i) the encoded image embedding, (ii) the image tokens, or (iii) the textual label. The output images are provided for output.
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 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using geographical or spatial information, e.g. location
48.
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 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
42 - Scientific, technological and industrial services, research and design
Goods & 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 - Processes or apparatus for separating the constituents of gaseous mixtures involving the use of liquefaction or solidification by rectification, i.e. by continuous interchange of heat and material between a vapour stream and a liquid stream
09 - Scientific and electric apparatus and instruments
38 - Telecommunications services
42 - Scientific, technological and industrial services, research and design
Goods & 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 - Scientific and electric apparatus and instruments
38 - Telecommunications services
42 - Scientific, technological and industrial services, research and design
Goods & 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 - Scientific, technological and industrial services, research and design
Goods & 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.
54.
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.
G01J 5/07 - Arrangements for adjusting the solid angle of collected radiation, e.g. adjusting or orienting field of view, tracking position or encoding angular position
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 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.
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.
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.
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 - Strategic management or analysis, e.g. setting a goal or target of an organisationPlanning actions based on goalsAnalysis or evaluation of effectiveness of goals
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 - Circuit arrangements or systems for wireless supply or distribution of electric power using light, e.g. lasers
H02J 50/40 - Circuit arrangements or systems for wireless supply or distribution of electric power using two or more transmitting or receiving devices
H04B 10/80 - Optical aspects relating to the use of optical transmission for specific applications, not provided for in groups , e.g. optical power feeding or optical transmission through water
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 - Resource planning, allocation, distributing or scheduling for enterprises or organisations
G06Q 10/0635 - Risk analysis of enterprise or organisation activities
G06Q 10/0637 - Strategic management or analysis, e.g. setting a goal or target of an organisationPlanning actions based on goalsAnalysis or evaluation of effectiveness of goals
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 - Investigating or analysing materials by specific methods not covered by groups
G06Q 10/0635 - Risk analysis of enterprise or organisation activities
G06Q 10/0637 - Strategic management or analysis, e.g. setting a goal or target of an organisationPlanning actions based on goalsAnalysis or evaluation of effectiveness of goals
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 - Treatment of water, waste water, or sewage by electrochemical methods by electrolysis
C02F 1/469 - Treatment of water, waste water, or sewage by electrochemical methods by electrochemical separation, e.g. by electro-osmosis, electrodialysis, electrophoresis
C02F 1/66 - Treatment of water, waste water, or sewage by neutralisationTreatment of water, waste water, or sewage pH adjustment
C02F 103/10 - Nature of the water, waste water, sewage or sludge to be treated from quarries or from mining activities
C02F 103/16 - Nature of the water, waste water, sewage or sludge to be treated from metallurgical processes, i.e. from the production, refining or treatment of metals, e.g. galvanic wastes
C02F 103/18 - Nature of the water, waste water, sewage or sludge to be treated from the wet purification of gaseous effluents
72.
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.
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 - Surveying specially adapted to open water, e.g. sea, lake, river or canal
G01N 21/31 - Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
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.
B28C 7/02 - Controlling the operation of the mixing
C04B 20/00 - Use of materials as fillers for mortars, concrete or artificial stone according to more than one of groups and characterised by shape or grain distributionTreatment of materials according to more than one of the groups specially adapted to enhance their filling properties in mortars, concrete or artificial stoneExpanding or defibrillating materials
C04B 40/00 - Processes, in general, for influencing or modifying the properties of mortars, concrete or artificial stone compositions, e.g. their setting or hardening ability
G01N 15/0205 - Investigating particle size or size distribution by optical means
G16C 60/00 - Computational materials science, i.e. ICT specially adapted for investigating the physical or chemical properties of materials or phenomena associated with their design, synthesis, processing, characterisation or utilisation
76.
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 - Scientific and electric apparatus and instruments
40 - Treatment of materials; recycling, air and water treatment,
42 - Scientific, technological and industrial services, research and design
45 - Legal and security services; personal services for individuals.
Goods & 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.
A photonic integrated circuit including an optical modulator, one or more waveguides, and an outcoupler is described. The optical modulator includes a modulation region and a modulation actuator. The modulation region includes an inhomogeneous arrangement of two or more different materials having different refractive indexes to structure the modulation region to manipulate one or more optical properties of an optical carrier wave in response to a modulation bias. The modulation actuator is disposed proximate to the modulation region and adapted to apply the modulation bias to the modulation region to generate a first signal and a second signal. The outcoupler is optically coupled to the one or more waveguides to receive the first signal and the second signal and further adapted to preserve the first signal and the second signal as a combined signal directed out of the photonic integrated circuit.
G02F 1/025 - Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulatingNon-linear optics for the control of the intensity, phase, polarisation or colour based on semiconductor elements having potential barriers, e.g. having a PN or PIN junction in an optical waveguide structure
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for improved image segmentation using hyperspectral imaging. In some implementations, a system obtains image data of a hyperspectral image, the image data comprising image data for each of multiple wavelength bands. The system accesses stored segmentation profile data for a particular object type that indicates a predetermined subset of the wavelength bands designated for segmenting different region types for images of an object of the particular object type. The system segments the image data into multiple regions using the predetermined subset of the wavelength bands specified in the stored segmentation profile data to segment the different region types. The system provides output data indicating the multiple regions and the respective region types of the multiple regions.
G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
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.
G06F 30/18 - Network design, e.g. design based on topological or interconnect aspects of utility systems, piping, heating ventilation air conditioning [HVAC] or cabling
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing tasks. One of the methods includes obtaining a prompt, obtaining a set of documents, generating an input, providing the input to a plurality of language models, generating a distribution from intermediate answers from the language models; and generating an answer to the prompt by performing a probabilistic inference over the distribution.
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing tasks. One of the methods includes obtaining a prompt, obtaining a set of documents, generating an input, providing the input to a plurality of language models, generating a distribution from intermediate answers from the language models; and generating an answer to the prompt by performing a probabilistic inference over the distribution.
The technology provides techniques for optimizing transistor-level placement using a hybrid approach involving reinforcement learning ("RL") in conjunction with an optimization technique. This can include implementing an iterative RL training process for an integrated circuit to train a RL agent, including the RL agent learning an ordering of transistors for the integrated circuit by placement of one transistor on an encoded grid per iteration. The RL agent iterates until all transistors for the integrated circuit are placed on tire encoded grid. Upon placing all the transistors on the encoded grid, one or more processors implement a solver module using the ordering of the transistors as an input. The solver module is configured to perform an optimization to minimize spacing between the transistors. The trained reinforcement learning agent can then be save in memory.
G06F 30/27 - Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
87.
METHODS OF PRODUCING AND RECYCLING FUNCTIONALIZED AGGLOMERATED SILICA
Disclosed herein is a functionalized granule including a plurality of fine particles and a coating, as well as systems configured to employ such functionalized granules. Also disclosed herein is a method including collecting a plurality of fine particles; and generating a plurality of functionalized granules using the plurality of fine particles, wherein an average dimension or a mean dimension of the plurality of functionalized granules is larger than an average dimension or a mean dimension of the plurality of fine particles.
B01J 20/28 - Solid sorbent compositions or filter aid compositionsSorbents for chromatographyProcesses for preparing, regenerating or reactivating thereof characterised by their form or physical properties
B01D 53/02 - Separation of gases or vapoursRecovering vapours of volatile solvents from gasesChemical or biological purification of waste gases, e.g. engine exhaust gases, smoke, fumes, flue gases or aerosols by adsorption, e.g. preparative gas chromatography
B01J 20/30 - Processes for preparing, regenerating or reactivating
42 - Scientific, technological and industrial services, research and design
Goods & Services
(1) 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.
09 - Scientific and electric apparatus and instruments
35 - Advertising and business services
38 - Telecommunications services
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable software for accessing, processing,
compressing, analyzing, organizing, formatting, and
displaying data in the field of environmental conditions,
climate, weather, geography, risk assessment, and insurance;
downloadable computer software and downloadable computer
software applications featuring advanced weather tools
utilizing geospatial imagery, high-tempo spatial resolution,
and high definition weather maps for predicting, analyzing,
and reporting weather, climate changes, and environmental
conditions; downloadable environmental reports in the field
of weather information, weather data analytics, forecasting
weather and climate change on the internet, through online
publishers, by email, and through mobile services;
downloadable software for accessing, displaying, and
analyzing geo-spatial and environmental data, environmental,
geography, and climate analytics and environmental,
geography, and climate related information; downloadable
computer software and downloadable computer software
applications featuring software utilizing geospatial
imagery, high-tempo spatial resolution, and high definition
images from satellites and maps for predicting, analyzing
and reporting changes to weather, geography, and to the
climate and environment; downloadable software for tracking,
measuring, predicting, and reporting on insights about
natural resources, environmental conditions, geography, and
public land usage; computer hardware for collecting data and
images about natural resources, environmental conditions,
geographic, and public land usage; downloadable software
using machine learning for processing, generating,
understanding, recognizing, editing and analyzing data,
images, sound, videos, messages, text, and information;
downloadable computer software for transmitting, processing,
manipulating or analyzing data; downloadable mobile
applications for transmitting, processing, manipulating or
analyzing data; downloadable computer software to enable
access to and provide analysis of geospatial data and
images, satellite images and airborne images; downloadable
software for detecting, identifying, measuring and analyzing
roofs, building structures, property, terrain and other
objects in the nature of structural material and contents of
buildings and land and conditions in the nature of damage
and need for repair or replacement; downloadable software
for use in analysis, predictive modeling, and creating
reports, relating to property damages, loss information,
climate changes, environmental conditions, weather events,
and catastrophes; downloadable software for accessing
information on risk for specific geographic regions of
catastrophic events, weather, climate, and environmental
events, world events, and other potential loss events;
downloadable risk modeling software for analyzing business
and financial risk; downloadable software for analyzing and
reporting climate, environment and disaster risk management;
downloadable software for creating and viewing reports and
maps about changes in environmental conditions and the
climate that have occurred at geographic locations;
downloadable and recorded computer software for accessing
downloadable databases for analyzing risk relating to
weather and other perils. Business research services and business analysis of data in
the field of environment, geography, climate, and weather
conditions and changes; business consulting services in the
field of environment, geography, climate, and weather
conditions and changes; business research and data analysis
services in the field of allocating resources for responses
to natural disasters; business consulting services in the
field of allocating resources for responses to natural
disasters; data processing services in the field of
environmental risk assessment; providing business
information in the field of business sustainability;
analyzing and compiling business data; compiling and
analyzing statistics, data and other sources of information
for business purposes. Telecommunications services, namely, the receiving and
transmitting of voice, data, graphics, images, audio and
video by means of telecommunications networks, wireless
communication networks and the internet; provision of
communications facilities for the transmission of voice,
data, graphics, images, audio and video; provision of online
access to databases allowing users to access, manipulate,
share, and prepare reports relating to geospatial images and
geospatial science; provision of online access to databases
allowing users to access, manipulate, share, and prepare
reports relating to data on weather, environmental
assessments, climate science, natural hazards, weather and
geological event modeling and simulation. Providing temporary use of on-line non-downloadable software
for accessing, processing, compressing, analyzing,
organizing, formatting, and displaying data in the field of
environmental conditions, climate, weather, geography, risk
assessment, and insurance; Platform as a Service (PaaS)
featuring advanced weather tools utilizing geospatial
imagery, high-tempo spatial resolution, and high definition
weather maps for predicting, analyzing, and reporting
weather, climate changes, and environmental conditions;
providing temporary use of on-line non-downloadable software
for accessing, displaying, and analyzing geo-spatial and
environmental data, environmental, geography, and climate
analytics and environmental, geography, and climate related
information; Platform as a Service (PaaS) featuring software
utilizing geospatial imagery, high-tempo spatial resolution,
and high definition images from satellites and maps for
predicting, analyzing and reporting changes to weather,
geography, and to the climate and environment; providing
temporary use of on-line non-downloadable software for
tracking, measuring, predicting, and reporting on insights
about natural resources, environmental conditions,
geography, and public land usage; providing temporary use of
on-line non-downloadable software using machine learning for
processing, generating, understanding, recognizing, editing
and analyzing data, images, sound, videos, messages, text,
and information; providing temporary use of on-line
non-downloadable software for transmitting, processing,
manipulating or analyzing data; Platform as a Service (PaaS)
featuring software to enable access to and provide analysis
of geospatial data and images, satellite images and airborne
images; Platform as a Service (PaaS) featuring software for
detecting, identifying, measuring and analyzing roofs,
building structures, property, terrain and other objects in
the nature of structural material and contents of buildings
and land and conditions in the nature of damage and need for
repair or replacement; providing temporary use of on-line
non-downloadable software for use in analysis, predictive
modeling, and creating reports, relating to property
damages, loss information, climate changes, environmental
conditions, weather events, and catastrophes; providing
temporary use of on-line non-downloadable software for
accessing information on risk for specific geographic
regions of catastrophic events, weather, climate, and
environmental events, world events, and other potential loss
events; providing temporary use of on-line non-downloadable
risk modeling software for analyzing business and financial
risk; providing temporary use of on-line non-downloadable
computer software for analyzing and reporting climate,
environment and disaster risk management; providing
temporary use of on-line non-downloadable software for
creating and viewing reports and maps about changes in
environmental conditions and the climate that have occurred
at geographic locations; providing temporary use of on-line
non-downloadable software for accessing downloadable
databases for analyzing risk relating to weather and other
perils; providing information and analytical reports, via an
interactive website, in the fields of weather, environmental
analysis, and climate science; providing information and
analytical reports, via a database, in the fields of
weather, environmental assessments, climate science, natural
hazards, weather and geological event modeling and
simulation; advanced product research in the field of
weather, environmental analysis, and climate science;
research in the field of weather, environmental analysis,
and climate science; professional consultancy in the field
of environmental conservation and protection; providing
information relating environmental preservation and
conservation issues and initiatives; technological planning
and consulting services in the field of environmental risk
assessment.
90.
AUTOMATIC DETECTION OF GRID-CONNECTED DISTRIBUTED ENERGY RESOURCES
Methods, systems, and apparatus, including computer programs encoded on a storage device, for determining whether a distributed energy resource is connected at a location. Electrical load data is obtained for a location over a time period. The electrical load data is analyzed to determine one or more signals from the electrical load data. The signals are compared to one or more load profiles for the location. Each load profile can indicate one or more baseline electrical patterns for the location. A likelihood that at least one distributed energy resource is in use at the location is determined based on the comparison. In response to determining that the likelihood is more than a threshold, one or more actions are performed.
42 - Scientific, technological and industrial services, research and design
Goods & 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; Data automation and collection service using proprietary software to evaluate, analyze and collect data for the purpose 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
92.
TECHNIQUES FOR ADDING AND REMOVING STRUCTURAL FEATURES DURING GRADIENT-BASED OPTIMIZATION
In some embodiments, a computer-implemented method for designing a physical device is provided. A computing system determines whether a feature from a list of features is present in a set of structural parameters by, in response to determining whether a feature presence function indicates that the feature should be included in the set of structural parameters or not, updating the set of structural parameters to include the feature or refraining from updating the set of structural parameters to include the feature, accordingly. The computing system simulates performance of the initial design using the set of structural parameters to determine a performance loss value, determines a structural gradient based on the performance loss value, determines a feature gradient based on the performance loss value, and updates the features in the list of features based on the structural gradient and the feature gradient.
G03F 7/00 - Photomechanical, e.g. photolithographic, production of textured or patterned surfaces, e.g. printed surfacesMaterials therefor, e.g. comprising photoresistsApparatus specially adapted therefor
G05B 19/4097 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by using design data to control NC machines, e.g. CAD/CAM
93.
ACTIVE SEISMIC SOURCE GENERATION FOR DISTRIBUTED ACOUSTIC SENSING, GEO-TAGGING, AND SUBSURFACE IMAGING
A system includes a mobile vehicle including a geolocator and an active acoustic source configured to generate acoustic wave energy directed toward a fiber optic network that includes one or more fiber optic cables and a distributed acoustic sensing (DAS) interrogator communicably coupled to the one or more fiber optic cables; and a control system. The control system is configured to perform operations including acquiring a signal from the DAS interrogator in response to the acoustic wave energy generated from the active acoustic energy source during movement of the mobile vehicle on or above the terranean surface; determining a geolocation of the mobile vehicle from the geolocator during or subsequent to acquisition of the signal from the DAS interrogator; and determining a location of the at least one fiber optic cable based on the determined geolocation of the mobile vehicle during acquisition of the signal from the DAS interrogator.
A system includes a mobile vehicle including a geolocator and an active acoustic source configured to generate acoustic wave energy directed toward a fiber optic network that includes one or more fiber optic cables and a distributed acoustic sensing (DAS) interrogator communicably coupled to the one or more fiber optic cables; and a control system. The control system is configured to perform operations including acquiring a signal from the DAS interrogator in response to the acoustic wave energy generated from the active acoustic energy source during movement of the mobile vehicle on or above the terranean surface; determining a geolocation of the mobile vehicle from the geolocator during or subsequent to acquisition of the signal from the DAS interrogator; and determining a location of the at least one fiber optic cable based on the determined geolocation of the mobile vehicle during acquisition of the signal from the DAS interrogator.
09 - Scientific and electric apparatus and instruments
38 - Telecommunications services
42 - Scientific, technological and industrial services, research and design
Goods & 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; none of the aforementioned in relation to vehicles, construction equipment and construction machines. 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.
The present disclosure relates to a suit with an integrated air supply. The suit includes a body comprising a first body portion and a second body portion, an air supply coupleable to the body, a coupling mechanism coupled to the body and arranged for releasably receiving the air supply. The coupling mechanism is disposed on the first body portion and the second body portion of the suit.
B63C 11/24 - Air supply carried by diver in closed circulation
A41D 13/012 - Professional, industrial or sporting protective garments, e.g. surgeons' gowns or garments protecting against blows or punches for aquatic activities, e.g. with buoyancy aids
This disclosure describes a system and method for a central controller layer to monitor conditions and control operations of an electric grid. The central controller layer communicates with an intermediate controller layer that includes hubs to monitor operations of grid edge devices connected to different regions of the electric grid. The central controller layer obtains, from each hub, sensor data corresponding to measurements performed by the grid edge devices. The central controller layer determines, based on the sensor data and expected grid-wide operations, control strategies with expected electrical operating conditions for the respective region, and provides a respective control strategy to each hub. In response to receiving the respective control strategy for the hub, each hub generates operational parameters for at least one grid edge device that cause a grid edge device to adjust its operation based on the expected amount of power flow for the hub.
Disclosed implementations relate to preserving individuals' semantic privacy while facilitating automation of tasks across a population of individuals. In various implementations, data indicative of an observed set of interactions between a user and a computing device may be recorded and used to simulate multiple different synthetic sets of interactions between the user and the computing device. Each synthetic set may include a variation of the observed set of interactions at a different level of abstraction. User feedback may be obtained about each of the multiple different sets. Based on the user feedback, one of the multiple different synthetic sets of interactions may be selected and used to train a machine learning model.
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.
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating synthetic training data representing network disruptions. One of the methods includes obtaining data representing one or more first travel time distributions between at the at least two entities in the supply chain network. Synthetic network disruption data is generated including sampling from one or more second travel time distributions corresponding respectively to one or more simulated network disruptions. A second dataset having the synthetic network disruption data is generated, and a network policy agent is trained using the second dataset.
