Enhanced systems, media and techniques that include the actions of applying a health monitoring device to a surface of a tissue of interest, the health monitoring device includes a microneedle array including a plurality of microneedles, where the plurality of microneedles includes functionalized microspheres. The techniques also includes collecting, by one or more microneedles of the plurality of microneedles, fluid corresponding to the tissue of interest, where collecting the fluid includes: facilitating, by one or more fluidic channels within the one or more microneedles, flow of the fluid from the tissue of interest to a sensing layer including a plurality of biomarker sensors.
A61B 5/145 - Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value
A61B 5/157 - Devices for taking samples of blood characterised by integrated means for measuring characteristics of blood
A61B 5/00 - Measuring for diagnostic purposes Identification of persons
A61B 10/00 - Instruments for taking body samples for diagnostic purposesOther methods or instruments for diagnosis, e.g. for vaccination diagnosis, sex determination or ovulation-period determinationThroat striking implements
A61M 37/00 - Other apparatus for introducing media into the bodyPercutany, i.e. introducing medicines into the body by diffusion through the skin
2.
MEMBRANELESS SYSTEMS FOR INORGANIC WASTE RECYCLING
The present disclosure relates to methods and systems for extracting non-alkali metal content from inorganic solid waste using membraneless regenerative electrochemical processes.
C25B 11/051 - Electrodes formed of electrocatalysts on a substrate or carrier
C25B 11/091 - Electrodes formed of electrocatalysts on a substrate or carrier characterised by the electrocatalysts material consisting of at least one catalytic element and at least one catalytic compoundElectrodes formed of electrocatalysts on a substrate or carrier characterised by the electrocatalysts material consisting of two or more catalytic elements or catalytic compounds
C25B 15/08 - Supplying or removing reactants or electrolytesRegeneration of electrolytes
C22B 7/00 - Working-up raw materials other than ores, e.g. scrap, to produce non-ferrous metals or compounds thereof
H01M 10/54 - Reclaiming serviceable parts of waste accumulators
3.
GRAPH NEURAL NETWORKS TO IMPROVE GROUND-BASED MONITORING
Disclosed herein are systems and methods for training a neural network generating seismic training data comprising at least three sets of training data: a first set that comprises training data that represents a simulated seismic event, and at least two second sets, each second set comprising training data of sensor values, each second set of sensor values corresponding to distinct simulated seismic observation systems, and each seismic value of each second set comprises an associated arrival time value; introducing a time offset to each arrival time value of each second set of seismic values to generate modified seismic training data; generating a plurality of graphs, each graph based on one set of training data from the first set of training data and the at least two sets of sensor values; and training the neural network using the plurality of graphs as input.
G01V 1/28 - Processing seismic data, e.g. for interpretation or for event detection
G01V 1/36 - Effecting static or dynamic corrections on records, e.g. correcting spreadCorrelating seismic signalsEliminating effects of unwanted energy
4.
PLATFORMS, SYSTEMS, AND METHODS FOR TRAINING MACHINE LEARNING MODELS WITH SPECIALIZED DATA
According to one aspect, there is provided a computer-implemented method for training artificial intelligence models with specialized biologic data in an AI-guided analytic platform for development of a biologic synthesis process, comprising: collecting multimodal biologic data including at least one of a gene expression level, mRNA, metabolic reaction fluxes, or intracellular metabolite concentrations from biologic systems; processing the collected biologic data through data normalization and quality assurance steps to create model-ready data; and generating at least one output predicting an effect of genetic modification on a metabolite level or a reaction flux.
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
C12M 1/00 - Apparatus for enzymology or microbiology
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 method may select at least two objectives of the product. The method may select a parent of the product. The method may determine the product based on an evaluation of the at least two objectives for a set of variants of the parent.
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
C12M 1/00 - Apparatus for enzymology or microbiology
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
Methods, systems, and apparatus, including computer programs encoded on a storage device, for identifying characteristics of electric grid assets are disclosed. A method includes obtaining a plurality of images, each image depicting at least one utility pole of an electric grid; detecting, in each of the plurality of images, keypoints of the at least one utility pole depicted in the image; determining, using the keypoints from at least two images of a particular utility pole, at least one measurement of the particular utility pole; determining, using the measurement of the particular utility pole, an electrical characteristic of an asset supported by the particular utility pole; and providing the electrical characteristic as an output. The two or more images include images of the particular utility pole captured from multiple different camera perspectives. The asset can include a capacitor, a transformer, a switch, a power line.
G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
G06V 10/80 - Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
According to one aspect, there is provided a computer-implemented system for evaluating and improving strain production using three integrated components: a prototype system for evaluating candidate strains, an optimization system for enhancing strain performance, and a scale-up system for adapting laboratory results to commercial-scale parameters. The system employs artificial intelligence models trained on data from all three components. The system continuously receives performance data from these systems to update its AI models. Using these updated models, the system generates modified operational parameters for the prototype, optimization, and scale-up systems, creating a feedback loop for continuous process improvement.
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
C12M 1/00 - Apparatus for enzymology or microbiology
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 system may include a plurality of sensors configured to measure fermentation parameters. The system may include a control system operatively coupled to the fermentation chamber and the plurality of sensors, the control system comprising: at least one processor; memory storing instructions that, when executed by the at least one processor, cause the control system to: receive sensor data from the plurality of sensors; process the sensor data using a set of AI-based learning models to determine a set of improved fermentation parameters; generate control signals based on the determined set of improved fermentation parameters; and adjust operating conditions of the fermentation chamber based on the control signals.
A system may receive data from a plurality of sources. The system may perform a data quality assurance on the received data to identify at least one anomalous data point. The system may apply a Bayesian statistical normalization model to the data to: model a batch-specific systemic variation, account for a technical factor contributing to a batch effect, separate a signal from the technical factor; and generate normalized data. The system may output the normalized data for processing by a machine learning model.
A method may collect raw data on strain performance. The method may normalize the data using a probabilistic approach to generate normalized strain performance data. The method may represent strains as probability distributions over possible performance levels, wherein the probability distributions capture both a point estimate of the strain performance and uncertainty around the estimate. The method may define a hit based on the probability distributions by determining the strains having a specified probability of outperforming a parent strain by a predetermined margin. The method may identify a promising strain for further investigation based on the defined hit.
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
C12M 1/00 - Apparatus for enzymology or microbiology
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 system may include data integration facilities for integrating content of publication data sets relating to strains and proprietary data sets including parameters of a process in which the strain produces functional outputs, wherein integrated data is input to machine learning models. The machine learning models generate recommendations relating to modifications of the strain.
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
C12M 1/00 - Apparatus for enzymology or microbiology
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 computer-implemented method executed by one or more processors includes receiving interconnection data for a proposed interconnection to a power grid; accessing a power grid model including a topological representation of the power grid, electrical specifications of grid components, and empirical operation characteristics; and generating, using the interconnection data for the proposed interconnection to the power grid, and the power grid model, simulated power grid data. The simulated power grid data is based on simulating operation of the power grid with the proposed interconnection coupled to a location of the power grid identified by the interconnection data during a simulated time period. The simulated power grid data includes a plurality of different temporal and spatially dependent characteristics of the power grid. The method includes evaluating, using one or more metrics, the simulated power grid data; and outputting evaluation results of the one or more metrics.
A computer-implemented method executed by one or more processors includes receiving interconnection data for a proposed interconnection to a power grid; accessing a power grid model including a topological representation of the power grid, electrical specifications of grid components, and empirical operation characteristics; and generating, using the interconnection data for the proposed interconnection to the power grid, and the power grid model, simulated power grid data. The simulated power grid data is based on simulating operation of the power grid with the proposed interconnection coupled to a location of the power grid identified by the interconnection data during a simulated time period. The simulated power grid data includes a plurality of different temporal and spatially dependent characteristics of the power grid. The method includes evaluating, using one or more metrics, the simulated power grid data; and outputting evaluation results of the one or more metrics.
A system may include one or more processors and memory storing instructions that, when executed by the one or more processors, cause a platform to: identify an appropriate analytic method based on an assessment of a data characteristic, implement a data preparation procedure specific to a particular application, apply a machine learning model to analyze data and generate a prediction, perform a model validation procedure to ensure analytical reliability, create an audit trail documenting an analytic procedure and result; and generate technical documentation and visualization of an analytic finding.
Implementations are described herein for querying proprietary data using generative model(s). In various implementations, a first input prompt may be assembled to include a query for generative model(s). The first input prompt may be processed using generative model(s) to generate reference model output. Proprietary data source(s) may be identified for use in prompting generative model(s), and a second input prompt may be assembled to include the query and proprietary data from one or more of the proprietary data sources. The second input prompt may be processed using generative model(s) to generate at least partially exogenous model output based at least in part on the proprietary data. The reference and at least partially exogenous model outputs may then be compared to determine information gain score(s) associated with the proprietary data source(s). These information gain scores may be used for various purposes.
According to one aspect, there is provided an AI-based platform which may include an experiment data set including records that respectively represent an experiment. Each record may indicate at least one hypothesis associated with the experiment and an experiment definition based on the at least one hypothesis. An AI-based agent may be configured to perform an evaluation of respective records of each experiment, and generate, based on the evaluation, at least one observation about the at least one hypothesis associated with the experiment represented by each of the respective records.
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.
A system may include a data collection facility that collects strain data including biological information for multiple biological strain candidates and receives assay data from experiments. A prototype prediction system generates initial fitness predictions using first AI models trained on historical performance data and identifies an initial strain candidate subset. A scale-up prediction system receives assay data for the initial candidates, analyzes this data using second AI models to generate scale-up performance predictions for bioreactor production conditions, and selects strain candidates for production based on these predictions.
G16B 5/00 - ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
A system may select a first feature and a second feature of the biologic product. The system may determine a first biologic parent having the first feature and not having the second feature, wherein the first feature is based on an aspect of the first biologic parent. The system may determine a second biologic parent having the second feature and not having the first feature, wherein the second feature is based on an aspect of the first biologic parent, and the aspect of the second biologic parent can be combined with the aspect of the first biologic parent. The system may determine a biologic product having the first feature and the second feature, wherein the biologic product is determined based on an evaluation of a set of combinations of the aspect of the first biologic parent and the aspect of the second biologic parent.
G16B 20/00 - ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
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
20.
PLATFORMS, SYSTEMS, AND METHODS FOR PERFORMANCE PREDICTION USING MACHINE LEARNING MODELS
A method performed by one or more computers may comprise: receiving information about an entity; generating a set of representations based on the information about the entity; generating a set of edits of the entity based on the set of representations; and generating a performance prediction for each edit of the set of edits of the entity based on a pre-trained generalization machine learning model applied to each edit of the set of edits.
A machine learning system configured to: generate viability predictions by analyzing predicted performance and process conditions using one or more machine learning models; and prioritize development of entities based on the predicted performance and the viability predictions.
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
Methods, systems, and apparatus, including medium-encoded computer program products, for processing data representing a graph through each of a plurality of layers of a graph neural network to generate an output. The plurality of layers include a graph recursive convolutional layer.
According to one aspect, there is provided a method performed by one or more computers of generating a product of a synthesis process, comprising: selecting a parent of the product; identifying at least two objectives of the product, wherein each objective of the at least two objectives is based on a techno-economic analysis of the synthesis process; and determining a variant of the product based on the techno-economic analysis of the synthesis process.
G16B 5/00 - ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
G06Q 30/0201 - Market modellingMarket analysisCollecting market data
24.
PLATFORMS, SYSTEMS, AND METHODS TO CORRECT BATCH EFFECTS IN MACHINE LEARNING TRAINING BY ITERATIVE SPLITTING
A method may receive experimental data from a plurality of experiments. The method may detect a systematic variation between the experiments that is not related to a factor of interest. The method may apply a data normalization technique to minimize batch-specific systemic variation while preserving underlying signals. The method may generate probability distributions representing experimental outcomes to provide a summary of uncertainty. The method may use a machine learning model to identify and correct batch effects directly from the data without requiring explicit modeling of all possible sources of variation. The method may output normalized data with reduced batch effects.
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
25.
PLATFORMS, SYSTEMS, AND METHODS FOR AUTOMATED OMICS
A system receives data from analytical and mass spectrometry instruments, including measurement data from control and test samples. Computing hardware extracts peak lists comprising test and control peak lists from the received data and compresses them using a compression algorithm. The system provides mass-to-charge ratios and retention times associated with peaks from compressed peak lists to AI-based learning models trained to identify metabolites. The computing hardware identifies metabolites associated with the peaks and calculates corresponding peak areas. For each identified metabolite, the system generates a calibration curve based on calculated areas from compressed control peak lists and known concentrations. The system then calculates concentrations for identified metabolites from compressed test peak lists using these calibration curves, and generates a compilation of results.
09 - Scientific and electric apparatus and instruments
35 - Advertising and business services
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable software for use in connection with utilities,
namely, for providing information and analyzing data on
energy usage, renewable energy, energy savings, energy
distribution, energy transmission, energy measurement,
inter-connection of energy assets, utilities assets,
utilities repairs, route optimization, data optimization,
customer service, energy finance, and energy forecasting;
downloadable software utilizing artificial intelligence and
machine learning for use in connection with utilities
services and assets, namely, for providing customers with
access to utility account data and for providing
information, contextual prediction, personalization,
predictive analytics, and analyzing data and metrics on
energy usage, inter-connection of energy assets, renewable
energy, energy savings, energy distribution, energy
transmission, energy measurement, utilities assets,
utilities repairs, route optimization, data optimization,
customer service, energy finance, and energy forecasting;
downloadable software for computing energy usage, savings,
distribution, transmission, measurement, and forecasting;
downloadable simulation software for modeling, planning,
designing, operating, and optimizing utilities services,
utilities assets, energy grids, energy inter-connections,
renewable energy grids, energy distribution, energy
transmission, energy measurements, and also for energy
forecasting; downloadable application programming interface
(API) software; downloadable software development kits
(SDK). Business consulting services in the fields of electrical
grids, energy usage, renewable energy, inter-connection of
energy assets, energy usage management, and energy savings;
business consulting services in the field of energy
measurement to improve energy efficiency within residential,
commercial, industrial and institutional facilities;
providing business information in the fields of energy usage
management, electrical grids, inter-connection of energy
assets, energy savings in the nature of energy efficiency,
and energy measurement. Research, design and development of computer hardware and
software; computer services, namely, operating computer
systems and computer networks featuring energy transmission,
distribution, and management software for public utilities
and others for energy usage, renewable energy, energy
savings, energy distribution, energy transmission, energy
measurement, inter-connection of energy assets, utilities
assets, utilities repairs, route optimization, data
optimization, customer service, energy finance, and energy
forecasting; providing on-line non-downloadable software for
computing energy usage, savings, distribution, transmission,
measurement, and forecasting; providing on-line
non-downloadable software utilizing artificial intelligence,
and machine learning for use in connection with utilities
services and assets, namely, for providing customers with
access to utility account data and allowing customers to pay
utility bills and for providing information, contextual
prediction, personalization, predictive analytics, and
analyzing data and metrics on energy usage, inter-connection
of energy assets, renewable energy, energy savings, energy
distribution, energy transmission, energy measurement,
utilities assets, utilities repairs, route optimization,
data optimization, customer service, energy finance, and
energy forecasting; providing online non-downloadable
simulation software for modeling, planning, designing,
operating, and optimizing utilities services, utilities
assets, energy grids, energy inter-connections, renewable
energy grids, energy distribution, energy transmission,
energy measurements, and also for energy forecasting;
research and development of computer software; consulting
services in the fields of energy measurement to improve
energy efficiency; energy usage management.
27.
PLATFORMS, SYSTEMS, AND METHODS FOR GENETIC GENERALIZATION EXPRESSION LANGUAGES
A system may receive information about a biologic product, wherein the information includes a description of at least a portion of the biologic product in an expression language. The system may generate a set of edits of the biologic product based on the description the at least a portion of the biologic product in the expression language. The system may generate a performance prediction for each edit of the set of edits of the biologic product based on a pre-trained genetic generalization model applied to each edit of the set of edits.
G16B 5/00 - ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
G16B 25/10 - Gene or protein expression profilingExpression-ratio estimation or normalisation
Aspects of the disclosure relate to identifying potential areas of innovations utilizing machine learning models such as LLMs. As an example, a plurality of application areas and a plurality of sources may be identified. A model may be used to score pairs of each one of the plurality of application areas with respect to each one the plurality of sources. A matrix of the scores may be generated and provided for display to a user.
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for characterization of aggregate particles. A method includes obtaining, from a set of low fidelity sensors, first sensor data of a first portion of particles; obtaining, from a set of high fidelity sensors, second sensor data of the first portion of particles, the second sensor data comprising a higher fidelity representation of characteristics of the first portion of particles than the first sensor data; training a characterization model using the first sensor data and the second sensor data, the training comprising: providing, as training data to the characterization model, the second sensor data; and processing the second sensor data with the characterization model to correlate the first sensor data with the second sensor data. The first sensor data can indicate shape characteristics of each particle; and the second sensor data indicates a surface area of each particle.
Platforms, systems, and methods for rapid fermenter sampling. According to one aspect, there is provided A rapid sampling system for obtaining samples from a fermentation system, comprising: a sample inlet fluidly connected to the fermentation system; a pump fluidly connected to the sample inlet and configured to draw a sample from the fermentation system; a first valve fluidly connected to an outlet of the pump; a second valve fluidly connected to a liquid nitrogen chamber; a multi-well filter plate, wherein an individual well of the multi-well filter plate is configured to collect and filter the sample; a motorized base operatively connected to the multi-well filter plate configured to adjust a position of the multi-well filter plate; and a control unit including one or more processors and one or more memories operatively connected to the pump, the first valve, the second valve, and the motorized base.
This disclosure describes forecasting required power output for a plurality of thermal generators. Including training a Time-series Dense Encoder (TiDE) model on a corpus of historical weather data for a particular geographic region, the trained TiDE model forecasts weather for the geographic region. Training a machine learning model on historical power output and weather data for a particular wind farm within the geographic region, wherein the trained machine learning model predicts the power output out of the wind farm for a given weather condition. Forecasting, using the TiDE model, the weather in the geographic region. Predicting the power output of the wind farm by providing the forecasted weather to the machine learning model. Forecasting a required power output for a plurality of thermal generators based on the predicted power output of the wind farm by calculating the output of a fixed effects ordinary least squares (OLS) regression model.
Methods, systems, and apparatus for receiving a request for a risk assessment for a parcel, receiving a set of images for the parcel, the set of images including two or more images, each image having an image scale and an image resolution that is different from other images in the set of images, providing a first-level feature embedding and a second-level feature embedding, the first-level feature embedding being provided by processing a first-level image through a first-level machine learning (ML) model, and the second-level feature embedding being provided by processing a second-level image through a second-level ML model, determining a risk assessment at least partially by processing each of the first-level feature embedding and a second-level feature embedding through a fusion network, and providing a representation of the risk assessment for display.
G06V 10/80 - Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
The present disclosure relates to techniques including real-time prediction of a presence and/or an amount of Ethylene Vinyl Alcohol (EVOH) based on one or more hyperspectral images of an object or feedstock being processed in real-time (e.g., in a recycling workflow). The feedstock includes e.g., one or more EVOH-free and EVOH-based items, potentially comprising EVOH as a barrier layer. In some aspects, the disclosed techniques include accessing the one or more hyperspectral images associated with a three-dimensional space comprising one spectral dimension and two spatial dimensions acquired via one or more hyperspectral sensors. At least part of the feedstock may be processed via an EVOH detection model predicting a presence of EVOH and an EVOH quantification model to predict a variable corresponding to the amount of EVOH. Based on the predicted variable, the feedstock being automatically moved and processed as part of a recycling handling process, may be routed.
B07C 5/342 - Sorting according to other particular properties according to optical properties, e.g. colour
B29B 17/02 - Separating plastics from other materials
G01N 21/31 - Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
G01N 21/84 - Systems specially adapted for particular applications
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining segments from a sequence of text. One of the methods includes obtaining data representing a sequence of text; dividing the sequence of text into a plurality of sentence fragments; determining split scores comprising determining a split score for each of a plurality of pairs of sentence fragments formed from the plurality of sentence fragments; assigning one or more split positions based on the split scores; and combining the plurality of sentence fragments back into at least two segments, with a boundary of at least one of the at least two segments being identified by one of the one or more split positions, and wherein each segment comprises one or more sentence fragments.
Platforms, systems, and methods for model-in-the-loop synthetic biology. According to one aspect, there is provided an AI-based platform, comprising: an experiment data set defining a synthetic biology experiment based on a model of a biologic process; and an AI-based agent configured to, generate an experiment definition for the synthetic biology experiment based on the model of the biologic process, cause the synthetic biology experiment to be performed based on the experiment definition, perform an evaluation of at least one outcome of the synthetic biology experiment, and update the model of the biologic process based on the evaluation.
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
36.
USING ARTIFICIAL INTELLIGENCE FOR BUILDING DESIGN SPECIFICATION GENERATION
Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for automatic generation of building design specifications. Building design data for a plurality of buildings is obtained as building design artificial intelligence model training data. The building design artificial intelligence model training data is enhanced to include building performance specification data corresponding to obtained building design data. An artificial intelligence model is trained using the building design artificial intelligence model training data to generate building design specifications based on building performance specifications. Building performance specifications for a building project are received and provided to the artificial intelligence model that is trained to generate building design specifications based on building performance specifications. The artificial intelligence model generates building designs for the building project that satisfy the building performance specifications. The building designs for the building project are provided for evaluation and construction of the building project.
G06F 30/13 - Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
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
37.
PLATFORMS, SYSTEMS, AND METHODS FOR AUTOMATED OMICS FOR GENERALIZATION USING SPECTRAL DATABASES IN SYNTHETIC BIOLOGY DEVELOPMENT
Platforms, systems, and methods for automated omics for generalization using spectral databases in synthetic biology development. According to one aspect, there is provided a system for converting raw data from an analytical and mass spectrometry instrument to model-ready data, comprising: computing hardware configured to: receive data from the analytical and mass spectrometry instrument, wherein the data includes measurement data from a set of control samples and a set of test samples; extract a set of peak lists comprising a set of test peak lists and a set of control peak lists from the received data; compress the extracted peak lists using a compression algorithm; identify a set of metabolites that correspond to a set of peaks from the compressed peak lists by comparing a set of mass-to-charge ratios and a set of retention times associated with the set of peaks with the mass-to-charge ratios.
Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for generation of computer-executable code for automated zoning compliance. Zoning, building, planning, and other regulations for a jurisdiction are provided to a trained artificial intelligence model which provides computer-executable code that is configured, when executed, to provide output that indicates whether an input candidate building plan complies with the regulations for the jurisdiction. The computer-executable code generated by the trained artificial intelligence model is deployed in an application. The application receives, in a request, a candidate building plan. The application generates and provides a compliance report for the candidate building plan that includes compliance results for the candidate building plan with respect to the regulations for the jurisdiction.
G06F 30/13 - Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
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
39.
TRANSFORMER-DRIVEN DIFFERENTIABLE IMAGE RASTERIZATION FOR GENERATING VECTOR GRAPHICS
Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for transformer-driven differentiable image rasterization for generating vector graphics. An example method includes identifying a differentiable image rasterization library that includes a set of mathematically differentiable shape operations for creating a raster image. A set of image embeddings is received for an input image from an image encoder. The set of image embeddings and a prompt are provided to a transformer model. The prompt prompts the transformer model to generate transformer embeddings and map the transformer embeddings to input parameters of shape operations of the library. Mappings received from the transformer are provided to the library. A reconstructed image is received from the library that is generated from invoking shape operations of the library in accordance with the mappings. The reconstructed image is compared to the input image to generate reconstruction error data for training the transformer model.
A photonic grating coupler includes at least one waveguide port and a multi-layer material stack. The multi-layer material stack includes a first mixed material layer forming an upper inverse design region in which an upper grating pattern is disposed and a second mixed material layer disposed below the first mixed material layer. The second mixed material layer forms a lower inverse design region in which a lower grating pattern is disposed. The first and second waveguide ports physically abut to and extend from the second mix material layer and the upper and lower grating patterns are structured to collectively couple an optical signal incident on the photonic grating coupler from above the first mixed material layer into the at least one waveguide port.
Platforms, systems, and methods for multi-objective optimization and comparative analysis for synthetic biology development. According to one aspect, there is provided an AI-guided analytic platform for development of biologic synthesis processes, comprising: a multi-objective optimization system for performing multi-objective optimizations of the biologic synthesis processes; at least one multi-objective evaluation artificial intelligence model configured to evaluate a biologic product according to each of at least two objectives; and at least one variant evaluation module configured to: generate a set of variants of a biologic parent of the biologic product, and evaluate each variant of the set of variants of the biologic parent using the at least one multi-objective evaluation artificial intelligence model.
Platforms, systems, and methods for multi-objective optimization and comparative analysis for synthetic biology development. According to one aspect, there is provided a method of generating a biologic product of a biologic synthesis process, comprising: selecting a first biologic parent having a first feature; selecting a second biologic parent having a second feature; and selecting the biologic product based on an evaluation of a set of combinations of the first biologic parent and the second biologic parent.
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
43.
META-LEARNING FOR DETECTING OBJECT ANOMALY FROM IMAGES
Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for training a classification neural network. The system generates, from a set of object-specific data, one or more meta-learning datasets for one or more respective initial training tasks. The system determines values for a set of meta parameters by performing meta-learning with a classification neural network on the one or more meta-learning datasets. The system obtains a set of labeled training examples for a characteristic-detection task. The system determines based at least on one of the values for the set of meta parameters and using the set of labeled training examples, target values for the network parameters for the classification neural network to perform the characteristic-detection task.
Platforms, systems, and methods for pathway optimization for process bottlenecks in synthetic biology development. According to one aspect, there is provided a method of optimizing a biologic synthesis process, comprising: identifying at least one bottleneck in the biologic synthesis process; evaluating a set of variants of the biologic synthesis process; and selecting an adjusted biologic synthesis process, wherein the adjusted biologic synthesis process includes at least one variant of the set of variants that reduces the at least one bottleneck of the biologic synthesis process.
Provided herein are method of recycling metallic ion content from inorganic solid and systems thereof. The methods and systems include contacting inorganic solid with an acid to produce said concrete precursors.
C25B 1/34 - Simultaneous production of alkali metal hydroxides and chlorine, oxyacids or salts of chlorine, e.g. by chlor-alkali electrolysis
C25B 1/46 - Simultaneous production of alkali metal hydroxides and chlorine, oxyacids or salts of chlorine, e.g. by chlor-alkali electrolysis in diaphragm cells
C25B 9/17 - Cells comprising dimensionally-stable non-movable electrodesAssemblies of constructional parts thereof
C25B 9/19 - Cells comprising dimensionally-stable non-movable electrodesAssemblies of constructional parts thereof with diaphragms
C25B 9/21 - Cells comprising dimensionally-stable non-movable electrodesAssemblies of constructional parts thereof with diaphragms two or more diaphragms
C25B 9/23 - Cells comprising dimensionally-stable non-movable electrodesAssemblies of constructional parts thereof with diaphragms comprising ion-exchange membranes in or on which electrode material is embedded
C25B 15/08 - Supplying or removing reactants or electrolytesRegeneration of electrolytes
C25C 1/02 - Electrolytic production, recovery or refining of metals by electrolysis of solutions of light metals
C25C 1/06 - Electrolytic production, recovery or refining of metals by electrolysis of solutions of iron group metals, refractory metals or manganese
C25C 1/08 - Electrolytic production, recovery or refining of metals by electrolysis of solutions of iron group metals, refractory metals or manganese of nickel or cobalt
C25C 1/10 - Electrolytic production, recovery or refining of metals by electrolysis of solutions of iron group metals, refractory metals or manganese of chromium or manganese
C25C 1/12 - Electrolytic production, recovery or refining of metals by electrolysis of solutions of copper
C25C 1/14 - Electrolytic production, recovery or refining of metals by electrolysis of solutions of tin
C25C 1/16 - Electrolytic production, recovery or refining of metals by electrolysis of solutions of zinc, cadmium or mercury
C25C 1/18 - Electrolytic production, recovery or refining of metals by electrolysis of solutions of lead
C25C 1/20 - Electrolytic production, recovery or refining of metals by electrolysis of solutions of noble metals
C25C 1/22 - Electrolytic production, recovery or refining of metals by electrolysis of solutions of metals not provided for in groups
H01M 6/52 - Reclaiming serviceable parts of waste cells or batteries
H01M 10/54 - Reclaiming serviceable parts of waste accumulators
B01D 61/48 - Apparatus therefor having one or more compartments filled with ion-exchange material
Platforms, systems, and methods for genetic generalization in synthetic biology development. According to one aspect, there is provided a method for predicting performance associated with genetic edits, the method comprising: receiving, by a platform, information about a strain of a microorganism, wherein the information about the strain comprises information describing a plurality of genetic edits to a base strain of the microorganism; generating, by the platform, a set of genetic embeddings based on the information about the strain, wherein the generating comprises processing the information about the strain using one or more embedding models, wherein each of the one or more embedding models: receives the information about the strain of the microorganism as input; and applies computational transformations to the input using a corresponding embedding model to generate a multi-dimensional vector representation for each of the plurality of genetic edits.
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
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining segments from a sequence of text. One of the methods includes obtaining data representing a sequence of text; dividing the sequence of text into a plurality of sentence fragments; determining classification scores comprising determining a classification score using a machine learning model for each of a plurality of pairs of sentence fragments formed from the plurality of sentence fragments; assigning one or more split positions based on the classification scores; and combining the plurality of sentence fragments back into at least two segments, with a boundary of at least one of the at least two segments being identified by one of the one or more split positions, and wherein each segment comprises one or more sentence fragments.
09 - Scientific and electric apparatus and instruments
Goods & Services
Downloadable and recorded computer software for research,
modeling, data collection, data ingestion, data storage, and
simulations in the fields of biology, synthetic biology,
pharmaceutical preparations, biotechnology, living systems,
renewable materials, chemicals, organisms, and bioprocesses.
49.
DETECTING SURREPTITIOUS SPEECH USING MACHINE LEARNING MODELS
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for detecting surreptitious speech. One of the methods includes obtaining data representing a sequence of text; obtaining a sequence of tokens for the sequence of text comprising one or more groups of tokens, wherein each group comprises two or more tokens; processing the one or more groups of tokens using a first machine learning model to identify tokens that are out of context in the sequence of tokens; and providing data representing the identified tokens.
09 - Scientific and electric apparatus and instruments
35 - Advertising and business services
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable AI software for assisting in real estate
development, building construction, and architectural
design, generating pre-development building designs,
securing permitting and capital allocation for real estate
projects, real estate marketing, identifying building
locations and nature of real estate projects, and providing
operative construction drawings; downloadable AI software
for analyzing and compiling real estate, construction, and
architectural data, generating and enhancing models, and
generating text, images, audiovisual material, and document
in response to prompts; downloadable software utilizing
artificial intelligence for use in providing information and
predictive recommendations on real estate development,
building construction, and architectural design;
downloadable computer chatbot software for simulating
conversations; downloadable computer chatbot software for
assisting in real estate development, building construction,
and architectural design, generating pre-development
building designs, securing permitting and capital allocation
for real estate projects, real estate marketing, identifying
building locations and nature of real estate projects, and
providing operative construction drawings. Business advisory and information services in the fields of
architecture, real estate, interior design and urban
planning design; providing business planning and marketing
solutions for real estate professionals; real estate
marketing analysis; real estate sales management; business
research and data analysis services in the field of in the
fields of architecture, interior design and urban planning
design; business consulting services in the fields of
architecture, real estate, interior design and urban
planning design; data processing services in the fields of
architecture, real estate, interior design and urban
planning design; analyzing and compiling business data in
the fields of architecture, real estate, interior design and
urban planning design; compiling and analyzing statistics,
data and other sources of information for business purposes
in the fields of architecture, real estate, interior design
and urban planning design. Providing online non-downloadable software for assisting in
real estate development, building construction, and
architectural design, generating pre-development building
designs, securing permitting and capital allocation for real
estate projects, real estate marketing, identifying building
locations and nature of real estate projects, and providing
operative construction drawings; Software as a Service
(SaaS) services featuring software for assisting in real
estate development, building construction, and architectural
design, generating pre-development building designs,
securing permitting and capital allocation for real estate
projects, real estate marketing, identifying building
locations and nature of real estate projects, and providing
operative construction drawings; providing online
non-downloadable AI software for analyzing and compiling
real estate, construction, and architectural data,
generating and enhancing models, and generating text,
images, audiovisual material, and document in response to
prompts; Software as a Service (SaaS) services featuring AI
software for analyzing and compiling real estate,
construction, and architectural data, generating and
enhancing models, and generating text, images, audiovisual
material, and document in response to prompts; providing
online non-downloadable software utilizing artificial
intelligence for use in providing information and predictive
recommendations on real estate development, building
construction, and architectural design; Software as a
Service (SaaS) services featuring software utilizing
artificial intelligence for use in providing information and
predictive recommendations on real estate development,
building construction, and architectural design; providing
online non-downloadable computer chatbot software for
simulating conversations; providing online non-downloadable
computer chatbot software for assisting in real estate
development, building construction, and architectural
design, generating pre-development building designs,
securing permitting and capital allocation for real estate
projects, real estate marketing, identifying building
locations and nature of real estate projects, and providing
operative construction drawings; architectural services;
residential and commercial building design.
52.
PERFORMING FACT CHECKING USING MACHINE LEARNING MODELS
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing tasks. One of the methods includes receiving a trigger from a user; responsive to the trigger, obtaining text data representing one or more subwords to be processed; obtaining data representing a plurality of clusters, wherein each cluster comprises one or more documents of a plurality of documents; processing the text data to identify one or more clusters of the plurality of clusters that are relevant to the text data; for each of the one or more identified clusters: identifying one or more documents of the identified cluster that are relevant to the text data; identifying one or more documents that contradict the text data of the one or more identified documents that are relevant to the text data; and providing data representing the one or more identified documents that contradict the text data.
Techniques for generating a subsurface image include analyzing a region to be sensed to determine a plurality of reflector locations; and performing a survey. Performing the survey includes irradiating a plurality of reflectors positioned in the plurality of determined reflector locations with coherent electromagnetic energy; identifying one or more vibrations of the plurality of reflectors based on reflected electromagnetic energy from the plurality of reflectors; and generating survey data associated with the identified vibrations for at least one reflector of the plurality of reflectors. The techniques include providing the survey data as input to a machine learning algorithm; and generating, using the machine learning algorithm, a subsurface image associated with the region to be sensed.
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for detecting surreptitious speech. One of the methods includes obtaining data representing a sequence of text; obtaining a sequence of tokens for the sequence of text comprising one or more groups of tokens, wherein each group comprises two or more tokens; processing the one or more groups of tokens using a first machine learning model to identify tokens that are out of context in the sequence of tokens; and providing data representing the identified tokens.
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing tasks. One of the methods includes receiving a trigger from a user; responsive to the trigger, obtaining text data representing one or more subwords to be processed; obtaining data representing a plurality of clusters, wherein each cluster comprises one or more documents of a plurality of documents; processing the text data to identify one or more clusters of the plurality of clusters that are relevant to the text data; for each of the one or more identified clusters: identifying one or more documents of the identified cluster that are relevant to the text data; identifying one or more documents that contradict the text data of the one or more identified documents that are relevant to the text data; and providing data representing the one or more identified documents that contradict the text data.
09 - Scientific and electric apparatus and instruments
35 - Advertising and business services
42 - Scientific, technological and industrial services, research and design
Goods & Services
(1) Downloadable software for use in connection with utilities, namely, for providing information and analyzing data on energy usage, renewable energy, energy savings, energy distribution, energy transmission, energy measurement, inter-connection of energy assets, utilities assets, utilities repairs, route optimization, data optimization, customer service, energy finance, and energy forecasting; downloadable software utilizing artificial intelligence and machine learning for use in connection with utilities services and assets, namely, for providing customers with access to utility account data and for providing information, contextual prediction, personalization, predictive analytics, and analyzing data and metrics on energy usage, inter-connection of energy assets, renewable energy, energy savings, energy distribution, energy transmission, energy measurement, utilities assets, utilities repairs, route optimization, data optimization, customer service, energy finance, and energy forecasting; downloadable software for computing energy usage, savings, distribution, transmission, measurement, and forecasting; downloadable simulation software for modeling, planning, designing, operating, and optimizing utilities services, utilities assets, energy grids, energy inter-connections, renewable energy grids, energy distribution, energy transmission, energy measurements, and also for energy forecasting; downloadable application programming interface (API) software; downloadable software development kits (SDK). (1) Business consulting services in the fields of electrical grids, energy usage, renewable energy, inter-connection of energy assets, energy usage management, and energy savings; business consulting services in the field of energy measurement to improve energy efficiency within residential, commercial, industrial and institutional facilities; providing business information in the fields of energy usage management, electrical grids, inter-connection of energy assets, energy savings in the nature of energy efficiency, and energy measurement.
(2) Research, design and development of computer hardware and software; computer services, namely, operating computer systems and computer networks featuring energy transmission, distribution, and management software for public utilities and others for energy usage, renewable energy, energy savings, energy distribution, energy transmission, energy measurement, inter-connection of energy assets, utilities assets, utilities repairs, route optimization, data optimization, customer service, energy finance, and energy forecasting; providing on-line non-downloadable software for computing energy usage, savings, distribution, transmission, measurement, and forecasting; providing on-line non-downloadable software utilizing artificial intelligence, and machine learning for use in connection with utilities services and assets, namely, for providing customers with access to utility account data and allowing customers to pay utility bills and for providing information, contextual prediction, personalization, predictive analytics, and analyzing data and metrics on energy usage, inter-connection of energy assets, renewable energy, energy savings, energy distribution, energy transmission, energy measurement, utilities assets, utilities repairs, route optimization, data optimization, customer service, energy finance, and energy forecasting; providing online non-downloadable simulation software for modeling, planning, designing, operating, and optimizing utilities services, utilities assets, energy grids, energy inter-connections, renewable energy grids, energy distribution, energy transmission, energy measurements, and also for energy forecasting; research and development of computer software; consulting services in the fields of energy measurement to improve energy efficiency; energy usage management.
Methods, systems, and apparatus for receiving an image file recording an image and a set of metadata, determining a search space based on one or more of at least a portion of the set of metadata and auxiliary data, generating a set of candidate images based on the search space, identifying a candidate image in the set of candidate images as a best matching image relative to the image, the candidate image being associated with a set of candidate metadata, providing a set of augmented metadata for the image based on the set of metadata and the set of candidate metadata, the set of augmented metadata including at least a portion of the set of candidate metadata, and outputting a geographic features file that is generated using the set of augmented metadata, the geographic features file including data representing one or more geographic features represented in the image file.
09 - Scientific and electric apparatus and instruments
35 - Advertising and business services
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable software for use in connection with utilities, namely, for providing information and analyzing data on energy usage, renewable energy, energy savings, energy distribution, energy transmission, energy measurement, inter-connection of energy assets, utilities assets, utilities repairs, route optimization, data optimization, customer service, energy finance, and energy forecasting; Downloadable software utilizing artificial intelligence and machine learning for use in connection with utilities services and assets, namely, for providing customers with access to utility account data and for providing information, contextual prediction, personalization, predictive analytics, and analyzing data and metrics on energy usage, inter-connection of energy assets, renewable energy, energy savings, energy distribution, energy transmission, energy measurement, utilities assets, utilities repairs, route optimization, data optimization, customer service, energy finance, and energy forecasting; Downloadable software for computing energy usage, savings, distribution, transmission, measurement, and forecasting; Downloadable simulation software for modeling, planning, designing, operating, and optimizing utilities services, utilities assets, energy grids, energy inter-connections, renewable energy grids, energy distribution, energy transmission, energy measurements, and also for energy forecasting; Downloadable application programming interface (API) software for use in the field of utilities, utilities assets, electrical grids, energy, and renewable energy; Downloadable software development kits (SDK) for use in the field of utilities, utilities assets, electrical grids, energy, and renewable energy Consulting services in the fields of energy usage management and energy efficiency as it relates to electrical grids, energy usage, renewable energy, inter-connection of energy assets, and energy savings; Consulting services in the fields of energy consumption and usage conservation to improve energy efficiency; Business consulting services in the field of energy; Providing economic consultation in the field of energy; Business consulting services in the field of energy measurement to improve energy efficiency within residential, commercial, industrial and institutional facilities; Energy usage management; Providing information in the fields of energy usage management and energy efficiency as it relates to electrical grids, energy usage, renewable energy, inter-connection of energy assets, and energy savings Technological planning and consulting services in the field of renewable energy resources; Research, design and development of computer hardware and software for use in the fields of energy usage management and energy efficiency as it relates to electrical grids, energy usage, renewable energy, inter-connection of energy assets, and energy savings; Computer services, namely, operating computer systems and computer networks featuring energy transmission, distribution, and management software for public utilities and others for energy usage, renewable energy, energy savings, energy distribution, energy transmission, energy measurement, inter-connection of energy assets, utilities assets, utilities repairs, route optimization, data optimization, customer service, energy finance, and energy forecasting; Providing on-line non-downloadable software for computing energy usage, savings, distribution, transmission, measurement, and forecasting; Providing on-line non-downloadable software utilizing artificial intelligence, and machine learning for use in connection with utilities services and assets, namely, for providing customers with access to utility account data and allowing customers to pay utility bills and for providing information, contextual prediction, personalization, predictive analytics, and analyzing data and metrics on energy usage, inter-connection of energy assets, renewable energy, energy savings, energy distribution, energy transmission, energy measurement, utilities assets, utilities repairs, route optimization, data optimization, customer service, energy finance, and energy forecasting; Providing online non-downloadable simulation software for modeling, planning, designing, operating, and optimizing utilities services, utilities assets, energy grids, energy inter-connections, renewable energy grids, energy distribution, energy transmission, energy measurements, and also for energy forecasting; Research and development of computer software for use in the fields of energy usage management and energy efficiency as it relates to electrical grids, energy usage, renewable energy, inter-connection of energy assets, and energy savings; Consulting services in the fields of energy measurement to improve energy efficiency
09 - Scientific and electric apparatus and instruments
Goods & Services
(1) Downloadable and recorded computer software for research, modeling, data collection, data ingestion, data storage, and simulations in the fields of biology, synthetic biology, pharmaceutical preparations, biotechnology, living systems, renewable materials, chemicals, organisms, and bioprocesses.
60.
SOLVENT-BASED PROCESSES FOR FUNCTIONALIZED MATERIALS
Methods of producing functionalized materials are provided. Porous particles are introduced to a functionalization mixture including a volatile solvent. The functionalization mixture includes an adsorbing moiety including polyethylenimine, an interaction moiety including a silane moiety, a polymer, a crosslinking agent, a chelating agent, or an antioxidant. Porous particles are characterized by a porosity distribution between 100 and 200 nanometers and a diameter distribution between 0.8 and 3 millimeters. Functionalized particles are created through deposition of the functionalization mixture on a surface of a porous particle to form a surface modification layer. Compositions and functionalized materials are also provided.
B01J 20/28 - Solid sorbent compositions or filter aid compositionsSorbents for chromatographyProcesses for preparing, regenerating or reactivating thereof characterised by their form or physical properties
Methods and systems for using multiple hyperspectral cameras sensitive to different wavelengths to predict characteristics of objects for further processing, including recycling, are described. The multiple hyperspectral images can be used to predict higher resolution spectra by using a trained machine learning model. The higher resolution spectra may be more easily analyzed to sort plastics into a recyclability category. The hyperspectral images may also be used to identify and analyze dark or black plastics, which are challenging for SWIR, MWIR, and other wavelengths. The machine learning model may also predict the base polymers and contaminants of plastic objects for recycling. The hyperspectral images may be used to predict recyclability and other characteristics using a trained machine learning model.
G01J 3/40 - Measuring the intensity of spectral lines by determining density of a photograph of the spectrumSpectrography
G06V 10/56 - Extraction of image or video features relating to colour
G06V 10/774 - Generating sets of training patternsBootstrap methods, e.g. bagging or boosting
G06V 10/80 - Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
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
63.
FUNCTIONALISED MATERIALS FOR CARBON DIOXIDE SORPTION
Methods of producing functionalized materials are provided. Porous particles are introduced to a functionalization mixture including a volatile solvent. The functionalization mixture includes an adsorbing moiety including polyethylenimine, an interaction moiety including a silane moiety, a polymer, a crosslinking agent, a chelating agent, or an antioxidant. Porous particles are characterized by a porosity distribution between 100 and 200 nanometers and a diameter distribution between 0.8 and 3 millimeters. Functionalized particles are created through deposition of the functionalization mixture on a surface of a porous particle to form a surface modification layer. Compositions and functionalized materials are also provided.
B01J 20/10 - 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
Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for template-based building design optimization for building projects. Constraints for a building project are identified. Building design templates that meet the constraints are identified in a design template library. Building design options for the building project are automatically determined, based on identified building design templates. The building design options for the building project are evaluated based on building performance metrics. Selected building design options are selected based on evaluated building design options. A building plan is automatically generated for the building project that includes building designs that include selected building design options.
G06F 30/13 - Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
42 - Scientific, technological and industrial services, research and design
Goods & Services
Research and development of new products; providing
information on product research and product development via
a website; providing information in the fields of technology
and product design and development; providing technological
information on the use of technology to solve international
problems via a website; design and testing for new product
development; scientific and technological research and
development services; research and development in the field
of computer software and hardware; research and development
in the field of software and technology using artificial
intelligence and machine learning; development of new
technology for others in the field of artificial
intelligence and machine learning; development of new
technology for others in the field of environmental
sustainability, software automation, supply chain logistics,
communications and Internet access, utility access and
monitoring, and bioengineering.
66.
SUBTERRANEAN PARAMETER SENSING SYSTEMS AND METHODS
A carbon dioxide (CO2) sequestration sensor system includes an underground sub-assembly including one or more sensors configured to detect at least one attribute associated with CO2 sequestration below a terranean surface; and an above-ground sub-assembly positionable on the terranean surface proximate the underground sub-assembly and including at least one controller communicably coupled to the one or more sensors.
G01N 33/00 - Investigating or analysing materials by specific methods not covered by groups
E21B 41/00 - Equipment or details not covered by groups
E21B 47/117 - Detecting leaks, e.g. from tubing, by pressure testing
E21B 47/12 - Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling
G01V 1/18 - Receiving elements, e.g. seismometer, geophone
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating data items. One of the methods includes obtaining a conditioning input that characterizes a target seismic data item; and processing the conditioning input that characterizes the target seismic data item using a diffusion model that comprises a denoising neural network to generate the target seismic data item.
G01V 1/36 - Effecting static or dynamic corrections on records, e.g. correcting spreadCorrelating seismic signalsEliminating effects of unwanted energy
G06N 3/084 - Backpropagation, e.g. using gradient descent
09 - Scientific and electric apparatus and instruments
Goods & Services
Downloadable and recorded computer software for research, data collection, data ingestion, and data storage in the fields of biology, synthetic biology, pharmaceutical preparations, biotechnology, living systems, renewable materials, chemicals, organisms, and bioprocesses; downloadable and recorded computer simulation software using artificial intelligence (AI), machine learning, deep learning, and mechanistic and hybrid modeling for research, data collection, data ingestion, and data storage in the fields of biology, synthetic biology, pharmaceutical preparations, biotechnology, living systems, renewable materials, chemicals, organisms, and bioprocesses
Methods, systems, and apparatus are disclosed for electrical power grid visualization. A computer-implemented method includes: obtaining power grid data including different temporal and spatially dependent characteristics of a power grid, the characteristics including a first characteristic, a second characteristic, and a third characteristic; and generating a graphical user interface (GUI) representing a visualization of the power grid data. The GUI includes a line-diagram representation of power lines in the power grid overlaid on a map of a geographic region in which the power grid is located, the line-diagram including a plurality of line segments, wherein attributes of each line segment represent the power grid data at a particular spatial location of the power grid. The attributes include a time-changing thickness of the line segment representing the first characteristic; a plurality of time-changing directional arrows on the line segment representing the second characteristic; and a color shading representing the third characteristic.
H02J 13/00 - Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the networkCircuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training kinetic models on experimental data of biochemical pathways. In one aspect, a method comprises: receiving chemical reaction data for a biochemical pathway; automatically generating data defining a kinetic model of the biochemical pathway based on the chemical reaction data; obtaining experimental data for the biochemical pathway; training the kinetic model on the experimental data using a numerical optimization technique to optimize an objective function that measures a discrepancy between: (i) simulated data characterizing the biochemical pathway that is generated using the kinetic model, and (ii) the experimental data characterizing the biochemical pathway; and outputting the kinetic model of the biochemical pathway after training the set of kinetic model parameters.
G16C 20/10 - Analysis or design of chemical reactions, syntheses or processes
G16B 5/00 - ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
09 - Scientific and electric apparatus and instruments
35 - Advertising and business services
42 - Scientific, technological and industrial services, research and design
Goods & Services
(1) Downloadable AI software for assisting in real estate development, building construction, and architectural design, generating pre-development building designs, securing permitting and capital allocation for real estate projects, real estate marketing, identifying building locations and nature of real estate projects, and providing operative construction drawings; downloadable AI software for analyzing and compiling real estate, construction, and architectural data, generating and enhancing models, and generating text, images, audiovisual material, and document in response to prompts; downloadable software utilizing artificial intelligence for use in providing information and predictive recommendations on real estate development, building construction, and architectural design; downloadable computer chatbot software for simulating conversations; downloadable computer chatbot software for assisting in real estate development, building construction, and architectural design, generating pre-development building designs, securing permitting and capital allocation for real estate projects, real estate marketing, identifying building locations and nature of real estate projects, and providing operative construction drawings. (1) Business advisory and information services in the fields of architecture, real estate, interior design and urban planning design; providing business planning and marketing solutions for real estate professionals; real estate marketing analysis; real estate sales management; business research and data analysis services in the field of in the fields of architecture, interior design and urban planning design; business consulting services in the fields of architecture, real estate, interior design and urban planning design; data processing services in the fields of architecture, real estate, interior design and urban planning design; analyzing and compiling business data in the fields of architecture, real estate, interior design and urban planning design; compiling and analyzing statistics, data and other sources of information for business purposes in the fields of architecture, real estate, interior design and urban planning design.
(2) Providing online non-downloadable software for assisting in real estate development, building construction, and architectural design, generating pre-development building designs, securing permitting and capital allocation for real estate projects, real estate marketing, identifying building locations and nature of real estate projects, and providing operative construction drawings; Software as a Service (SaaS) services featuring software for assisting in real estate development, building construction, and architectural design, generating pre-development building designs, securing permitting and capital allocation for real estate projects, real estate marketing, identifying building locations and nature of real estate projects, and providing operative construction drawings; providing online non-downloadable AI software for analyzing and compiling real estate, construction, and architectural data, generating and enhancing models, and generating text, images, audiovisual material, and document in response to prompts; Software as a Service (SaaS) services featuring AI software for analyzing and compiling real estate, construction, and architectural data, generating and enhancing models, and generating text, images, audiovisual material, and document in response to prompts; providing online non-downloadable software utilizing artificial intelligence for use in providing information and predictive recommendations on real estate development, building construction, and architectural design; Software as a Service (SaaS) services featuring software utilizing artificial intelligence for use in providing information and predictive recommendations on real estate development, building construction, and architectural design; providing online non-downloadable computer chatbot software for simulating conversations; providing online non-downloadable computer chatbot software for assisting in real estate development, building construction, and architectural design, generating pre-development building designs, securing permitting and capital allocation for real estate projects, real estate marketing, identifying building locations and nature of real estate projects, and providing operative construction drawings; architectural services; residential and commercial building design.
72.
AUTOMATED KINETIC MODEL GENERATION FOR BIOCHEMICAL PATHWAYS
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training kinetic models on experimental data of biochemical pathways. In one aspect, a method comprises: receiving chemical reaction data for a biochemical pathway; automatically generating data defining a kinetic model of the biochemical pathway based on the chemical reaction data; obtaining experimental data for the biochemical pathway; training the kinetic model on the experimental data using a numerical optimization technique to optimize an objective function that measures a discrepancy between: (i) simulated data characterizing the biochemical pathway that is generated using the kinetic model, and (ii) the experimental data characterizing the biochemical pathway; and outputting the kinetic model of the biochemical pathway after training the set of kinetic model parameters.
G16B 5/00 - ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
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
Disclosed implementations relate to automating semantically-similar computing tasks across multiple contexts. In various implementations, an initial natural language input and a first plurality of actions performed using a first computer application may be used to generate a first task embedding and a first action embedding in action embedding space. An association between the first task embedding and first action embedding may be stored. Later, subsequent natural language input may be used to generate a second task embedding that is then matched to the first task embedding. Based on the stored association, the first action embedding may be identified and processed using a selected domain model to select actions to be performed using a second computer application. The selected domain model may be trained to translate between an action space of the second computer application and the action embedding space.
Computer-implemented methods may include accessing a multi-dimensional embedding space that supports relating embeddings of molecules to predicted values of a given property of the molecules. The method may also include identifying one or more points of interest within the embedding space based on the predicted values. Each of the one or more points of interest may include a set of coordinate values within the multi-dimensional embedding space and may be associated with a corresponding predicted value of the given property. The method may further include generating, for each of the one or more points of interest, a structural representation of a molecule by transforming the set of coordinate values included in the point of interest using a decoder network. The method may include outputting a result that identifies, for each of the one or more points of interest, the structural representation of the molecule corresponding to the point of interest.
C08J 11/16 - Recovery or working-up of waste materials of polymers by chemically breaking down the molecular chains of polymers or breaking of crosslinks, e.g. devulcanisation by treatment with inorganic material
C08J 11/10 - Recovery or working-up of waste materials of polymers by chemically breaking down the molecular chains of polymers or breaking of crosslinks, e.g. devulcanisation
G16C 10/00 - Computational theoretical chemistry, i.e. ICT specially adapted for theoretical aspects of quantum chemistry, molecular mechanics, molecular dynamics or the like
G16C 20/10 - Analysis or design of chemical reactions, syntheses or processes
G16C 20/20 - Identification of molecular entities, parts thereof or of chemical compositions
G16C 20/40 - Searching chemical structures or physicochemical data
G16C 20/70 - Machine learning, data mining or chemometrics
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
09 - Scientific and electric apparatus and instruments
35 - Advertising and business services
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable computer software using artificial intelligence (AI) for assisting in real estate development, building construction, and architectural design, generating pre-development building designs, securing permitting and capital allocation for real estate projects, real estate marketing, identifying building locations and nature of real estate projects, and providing operative construction drawings; Downloadable computer software using artificial intelligence (AI) for analyzing and compiling real estate, construction, and architectural data, generating and enhancing models, and generating text, images, audiovisual material, and document in response to prompts, all in the fields of real estate, building construction, and architecture; Downloadable computer software using artificial intelligence (AI) for providing information and predictive recommendations on real estate development, building construction, and architectural design; Downloadable computer chatbot software for simulating conversations; Downloadable computer chatbot software for assisting in real estate development, building construction, and architectural design, generating pre-development building designs, securing permitting and capital allocation for real estate projects, real estate marketing, identifying building locations and nature of real estate projects, and providing operative construction drawings Business advisory and information services in the fields of architecture, real estate, interior design and urban planning design; Providing business planning and marketing solutions for real estate professionals; Real estate marketing analysis; Real estate sales management; Business research and data analysis services in the fields of architecture, interior design, and urban planning design; Business consulting services in the fields of architecture, real estate, interior design and urban planning design; Data processing services in the fields of architecture, real estate, interior design and urban planning design; Analyzing and compiling business data in the fields of architecture, real estate, interior design and urban planning design; Compiling and analyzing statistics, data and other sources of information for business purposes in the fields of architecture, real estate, interior design and urban planning design Providing online non-downloadable software for assisting in real estate development, building construction, and architectural design, generating pre-development building designs, securing permitting and capital allocation for real estate projects, real estate marketing, identifying building locations and nature of real estate projects, and providing operative construction drawings; Software as a Service (SaaS) services featuring software for assisting in real estate development, building construction, and architectural design, generating pre-development building designs, securing permitting and capital allocation for real estate projects, real estate marketing, identifying building locations and nature of real estate projects, and providing operative construction drawings; Providing online non-downloadable software using artificial intelligence (AI) for analyzing and compiling real estate, construction, and architectural data, generating and enhancing models, and generating text, images, audiovisual material, and document in response to prompts, all in the fields of real estate, building construction, and architecture; Software as a service (SAAS) services featuring software using artificial intelligence (AI) for analyzing and compiling real estate, construction, and architectural data, generating and enhancing models, and generating text, images, audiovisual material, and document in response to prompts, all in the fields of real estate, building construction, and architecture; Providing online non-downloadable software using artificial intelligence (AI) for providing information and predictive recommendations on real estate development, building construction, and architectural design; Software as a service (SAAS) services featuring software using artificial intelligence (AI) for providing information and predictive recommendations on real estate development, building construction, and architectural design; Providing online non-downloadable computer chatbot software for simulating conversations; Providing online non-downloadable computer chatbot software for assisting in real estate development, building construction, and architectural design, generating pre-development building designs, securing permitting and capital allocation for real estate projects, real estate marketing, identifying building locations and nature of real estate projects, and providing operative construction drawings; Architectural services; Residential and commercial building design
Disclosed herein are systems and methods for objectively characterizing machine-learning models including receiving first training data formatted to be used in the training of a machine-learning model; receiving one or more challenge queries formatted to be run on the machine-learning model; generating, for the first training data, a plurality of associated training vectors that embed at least some of the first training data into a vector space; generating, for each of the one or more challenge queries, a plurality of associated challenge vectors that embed at least some of the challenge queries into the vector space; and determining, for each challenge query, a corresponding quality metric for the machine-learning model by determining a neighborhood density for each of the challenge queries in the vector space.
Methods, systems, and apparatus for receiving a request for a prediction relevant to an object of interest (OOI) in the geographic region, providing an attention guiding layer based on a location of the OOI within the geographic layer, the attention guiding layer including a matrix of pixels, each pixel having an attention value assigned thereto, retrieving a set of layers representative of the geographic region, processing the set of layers and the attention guiding layer by a ML model to generate the prediction relevant to the OOI, the ML model including a convolutional neural network (CNN), and providing a representation of the prediction for display.
G06V 10/25 - Determination of region of interest [ROI] or a volume of interest [VOI]
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
G06V 10/58 - Extraction of image or video features relating to hyperspectral data
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 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/70 - Labelling scene content, e.g. deriving syntactic or semantic representations
G06V 20/52 - Surveillance or monitoring of activities, e.g. for recognising suspicious objects
G06V 10/80 - Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
78.
TECHNIQUES FOR USING INVERSE DESIGN FOR COMBINED OPTIMIZATION OF OPTICAL AND ELECTRICAL COMPONENTS IN AN OPTOELECTRONIC MODULATOR
In some embodiments, a computer-implemented method for creating a design for an optoelectronic modulator device is provided. A computing system determines an initial design that includes optical structural parameters and electrical structural parameters for a design region. The computing system simulates electrical performance based on the electrical structural parameters to adjust optical characteristics of the optical structural parameters. The computing system simulates optical performance of the optical structural parameters having the adjusted optical characteristics to generate a performance loss value. The computing system determines a loss metric based on the performance loss value. The computing system backpropagates the loss metric to determine a structural gradient. The computing system revises at least one of the optical structural parameters and the electrical structural parameters based at least in part on the structural gradient to create an updated initial design.
G02F 1/01 - 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
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
G06F 30/20 - Design optimisation, verification or simulation
G06F 119/02 - Reliability analysis or reliability optimisationFailure analysis, e.g. worst case scenario performance, failure mode and effects analysis [FMEA]
79.
TECHNIQUES FOR USING INVERSE DESIGN FOR COMBINED OPTIMIZATION OF OPTICAL AND ELECTRICAL COMPONENTS IN AN OPTOELECTRONIC MODULATOR
In some embodiments, a computer-implemented method for creating a design for an optoelectronic modulator device is provided. A computing system determines an initial design that includes optical structural parameters and electrical structural parameters for a design region. The computing system simulates electrical performance based on the electrical structural parameters to adjust optical characteristics of the optical structural parameters. The computing system simulates optical performance of the optical structural parameters having the adjusted optical characteristics to generate a performance loss value. The computing system determines a loss metric based on the performance loss value. The computing system backpropagates the loss metric to determine a structural gradient. The computing system revises at least one of the optical structural parameters and the electrical structural parameters based at least in part on the structural gradient to create an updated initial design.
An integrated geomaterials preparation method including receiving, through an API of an integrated geomaterials preparation platform, a raw material request and a set of end-product parameters, determining, from the set of end-product parameters, required characteristics for at least one raw material ingredient to an end product to meet the raw material request, obtaining raw material sensor data from a plurality of raw material sensor systems, identifying, from the raw material sensor data, a particular raw material having characteristics similar to the required characteristics, where each sensor system is configured to scan and characterize raw materials, generating, using the characteristics of the particular raw material, operational parameters for geomaterial processing equipment to produce a raw material ingredient to meet the raw material request, and providing, the operational parameters to the geomaterial processing equipment, which when executed by the geomaterial processing equipment cause the geomaterial processing equipment to execute the operational parameters.
An integrated geomaterials preparation method including receiving, through an API of an integrated geomaterials preparation platform, a raw material request and a set of end-product parameters, determining, from the set of end-product parameters, required characteristics for at least one raw material ingredient to an end product to meet the raw material request, obtaining raw material sensor data from a plurality of raw material sensor systems, identifying, from the raw material sensor data, a particular raw material having characteristics similar to the required characteristics, where each sensor system is configured to scan and characterize raw materials, generating, using the characteristics of the particular raw material, operational parameters for geomaterial processing equipment to produce a raw material ingredient to meet the raw material request, and providing, the operational parameters to the geomaterial processing equipment, which when executed by the geomaterial processing equipment cause the geomaterial processing equipment to execute the operational parameters.
A thermally regulated photonic system includes a photonic component, a sensor adapted to measure a temperature related to the photonic component or a power output of the photonic component and generate a sensor value that is indicative of the temperature or the power output, a heat distribution system thermally coupled to the photonic component and adapted to generate and distribute heat to the photonic component, and a controller coupled to the sensor and the heat distribution system in a feedback loop configuration to thermally regulate the photonic component based upon the sensor value.
G02B 6/293 - 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
A thermally regulated photonic system includes a photonic component, a sensor adapted to measure a temperature related to the photonic component or a power output of the photonic component and generate a sensor value that is indicative of the temperature or the power output, a heat distribution system thermally coupled to the photonic component and adapted to generate and distribute heat to the photonic component, and a controller coupled to the sensor and the heat distribution system in a feedback loop configuration to thermally regulate the photonic component based upon the sensor value.
G02B 6/12 - 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
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 6/42 - Coupling light guides with opto-electronic elements
84.
FUNCTIONALIZED MATERIALS FOR CARBON CAPTURE AND SYSTEMS THEREOF
The present disclosure relates to a functionalized material, which may optionally be employed as a sorbent for carbon dioxide, as well as methods of making such materials and systems of using such materials. The processes, methods, and systems herein can be used for the separation of carbon dioxide from fluid streams.
B01D 53/83 - Solid phase processes with moving reactants
B01D 53/96 - Regeneration, reactivation or recycling of reactants
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 20/22 - Solid sorbent compositions or filter aid compositionsSorbents for chromatographyProcesses for preparing, regenerating or reactivating thereof comprising organic material
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 polarization rotating and beam splitting photonic device includes a planar waveguide having an input port and output ports disposed in or on a multi-layer semiconductor stack and a polarization rotating and beam splitting components integrated into the planar waveguide. The polarization rotating component includes a first irregular pattern of at least two materials having different refractive indexes. The first irregular pattern is shaped to rotate at least a portion of an optical signal received via the input port from a transverse magnetic (TM) polarization to a transverse electric (TE) polarization. The beam splitting component includes a second irregular pattern shaped to split the optical signal between the output ports. The first and second irregularly shaped patterns are optically coupled and collectively shaped to receive input TE and TM signals multiplexed on the optical signal at the input port and generate output TE signals demultiplexed on the output ports.
A polarization rotating and beam splitting photonic device includes a planar waveguide having an input port and output ports disposed in or on a multi-layer semiconductor stack and a polarization rotating and beam splitting components integrated into the planar waveguide. The polarization rotating component includes a first irregular pattern of at least two materials having different refractive indexes. The first irregular pattern is shaped to rotate at least a portion of an optical signal received via the input port from a transverse magnetic (TM) polarization to a transverse electric (TE) polarization. The beam splitting component includes a second irregular pattern shaped to split the optical signal between the output ports. The first and second irregularly shaped patterns are optically coupled and collectively shaped to receive input TE and TM signals multiplexed on the optical signal at the input port and generate output TE signals demultiplexed on the output ports.
G02B 6/126 - 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 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 27/28 - Optical systems or apparatus not provided for by any of the groups , for polarising
87.
GENERATING BOUNDING BOXES FOR GEOLOCALIZING OBLIQUE AERIAL IMAGERY
Methods, systems, and apparatus for receiving a first image file recording a first image and a first set of metadata associated with the first image, determining that the first image depicts a horizon, and in response, providing a modified first set of metadata by applying a visibility radius to a projection of the Earth depicted in the first image, determining a tangent line based on the visibility radius, and adjusting a height of the first image based on the tangent line to provide a modified height in the modified first set of metadata, and outputting a first geographic features file that is generated using the modified first set of metadata, the first geographic features file including data representing one or more geographic features represented in the first image file.
Methods, systems, and apparatus for receiving an image file recording an image and a set of metadata, determining a search space based on one or more of at least a portion of the set of metadata and auxiliary data, generating a set of candidate images based on the search space, identifying a candidate image in the set of candidate images as a best matching image relative to the image, the candidate image being associated with a set of candidate metadata, providing a set of augmented metadata for the image based on the set of metadata and the set of candidate metadata, the set of augmented metadata including at least a portion of the set of candidate metadata, and outputting a geographic features file that is generated using the set of augmented metadata, the geographic features file including data representing one or more geographic features represented in the image file.
G06F 16/58 - 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
89.
TOWARDS PREDICTION OF GEOMATERIAL PROPERTIES POST-PROCESSING VIA HIGH-THROUGHPUT CHEMICAL AND SPATIAL CHARACTERIZATION
Methods, systems, and apparatus, including computer programs encoded on a storage device, for determining characteristics of particles are disclosed. A system includes a conveyor belt, wherein a first section of the conveyor belt comprises one or more mechanisms arranged to create environmental conditions favorable to sensor reading. The system includes a sensor rig located proximate to the first section of the conveyor belt comprising a plurality of different types of sensors. The system includes a controller configured to: obtain measurement data from the plurality of different types of sensors; apply the measurement data to a machine learning model configured to determine surface chemical characteristics of particles given measurement data; and output the surface chemical characteristics of particles from the machine learning model to one or more components along the conveyor belt.
Disclosed herein are systems and methods for objectively characterizing machine-learning models including receiving first training data formatted to be used in the training of a machine-learning model; receiving one or more challenge queries formatted to be run on the machine-learning model; generating, for the first training data, a plurality of associated training vectors that embed at least some of the first training data into a vector space; generating, for each of the one or more challenge queries, a plurality of associated challenge vectors that embed at least some of the challenge queries into the vector space; and determining, for each challenge query, a corresponding quality metric for the machine-learning model by determining a neighborhood density for each of the challenge queries in the vector space.
The present disclosure relates to a method and system for acquiring and processing large unlabeled dataset of images to train an embedding model using a self-supervision technique, which may then be used to generate image embeddings with reduced dimensions for any downstream task or model. The downstream model can be a simple model and can be trained efficiently using a small, labeled training dataset as the embedding model may distill important information from the images of the small, labeled training dataset. According to present disclosure, the downstream task or model may include predicting a material category or quantity of a target material of interest in an image that captures (part or all of) one or more objects on a feedstock or a waste stream. In some instances, the image may correspond to a hyperspectral image that is collected using a camera system.
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
92.
GENERATING BOUNDING BOXES FOR GEOLOCALIZING OBLIQUE AERIAL IMAGERY
Methods, systems, and apparatus for receiving a first image file recording a first image and a first set of metadata associated with the first image, determining that the first image depicts a horizon, and in response, providing a modified first set of metadata by applying a visibility radius to a projection of the Earth depicted in the first image, determining a tangent line based on the visibility radius, and adjusting a height of the first image based on the tangent line to provide a modified height in the modified first set of metadata, and outputting a first geographic features file that is generated using the modified first set of metadata, the first geographic features file including data representing one or more geographic features represented in the first image file.
Computer-implemented techniques may include identifying a polymer for decomposition. For an ionic liquid, one or more properties corresponding to the polymer is accessed. One or more properties characterize a reaction between the polymer and the ionic liquid. A value of the property is accessed using a quantum-mechanical or thermodynamical method. A bond string and position (BSP) representation of a molecule of the ionic liquid is determined. An embedded representation of the ionic liquid is determined based on the BSP representation. A relationship between BSP representations of molecules and the one or more properties is generated. An ionic liquid is identified as a prospect for depolymerizing the specific polymer based on the relationship. An identification of the ionic liquid is output.
C08J 11/16 - Recovery or working-up of waste materials of polymers by chemically breaking down the molecular chains of polymers or breaking of crosslinks, e.g. devulcanisation by treatment with inorganic material
C08J 11/10 - Recovery or working-up of waste materials of polymers by chemically breaking down the molecular chains of polymers or breaking of crosslinks, e.g. devulcanisation
G16C 10/00 - Computational theoretical chemistry, i.e. ICT specially adapted for theoretical aspects of quantum chemistry, molecular mechanics, molecular dynamics or the like
G16C 20/10 - Analysis or design of chemical reactions, syntheses or processes
G16C 20/20 - Identification of molecular entities, parts thereof or of chemical compositions
G16C 20/40 - Searching chemical structures or physicochemical data
G16C 20/70 - Machine learning, data mining or chemometrics
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
42 - Scientific, technological and industrial services, research and design
Goods & Services
(1) Research and development of new products; providing information on product research and product development via a website; providing information in the fields of technology and product design and development; providing technological information on the use of technology to solve international problems via a website; design and testing for new product development; scientific and technological research and development services; research and development in the field of computer software and hardware; research and development in the field of software and technology using artificial intelligence and machine learning; development of new technology for others in the field of artificial intelligence and machine learning; development of new technology for others in the field of environmental sustainability, software automation, supply chain logistics, communications and Internet access, utility access and monitoring, and bioengineering.
Techniques for determining a mineralogy of a portion of a drainage basin include identifying topography data associated with a drainage basin comprising at least one body of water; identifying weather data associated with the drainage basin; identifying first sensor data associated with a first water sensor installed in the drainage basin; identifying second sensor data associated with a second water sensor that is located downstream of the first water sensor in the drainage basin; providing the first sensor data, second sensor data, topography data, and weather data as input to a machine learning algorithm; and determining, by the machine learning algorithm, a mineralogy of a portion of the drainage basin.
G01C 13/00 - 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
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
100.
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
