196 results about "Data value" patented technology

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for controlling data access. One of the methods includes receiving, from a user device associated with an account, a request for data; accessing data from one or more data sources that includes, for each of a plurality of data types, corresponding data values; selecting, from the plurality of data types and using permissions data for the account, one or more data types that the account has permission to access; and providing, to the user device and for each of the one or more data types that the account has permission to access, the corresponding data values.

System, apparatus, and computer program products are disclosed for protected display of a shared visual data object for an audiovisual conference session. In one aspect, a method includes receiving the shared visual data object, wherein the shared visual data object comprises visual data associated with one or more shared user interfaces; determining, using user interface generation circuitry and based on the shared visual data object, one or more protected data values associated with one or more protected data fields; generating, using the user interface generation circuitry, a masked visual data object based on each masked representation and each spatial coordinate set; and causing, using the user interface generation circuitry and / or the communications hardware, the masked visual data object to be displayed using the audiovisual conference session.

The application discloses a kind of blockchain unmanned plane telemetry processing data methods, belong to unmanned plane control technical field, including acquisition original telemetry data stream, type identification and semantic analysis are carried out based on preset telemetry data value evaluation model, the value classification of each frame telemetry data is realized, generates telemetry data chain request, carries out unmanned plane node mobility evaluation, dynamically selects consensus node, according to telemetry data value level selects matched chain strategy and priority uses consensus node and carries out hierarchical chain, based on preset exception rule library establishes exception detection model, real-time monitoring side chain on newly chained telemetry data, identifies flight abnormal event to carry out flight control and triggers alarm, can make that unmanned plane end power consumption reduces, improves data processing efficiency and resource utilization, guarantees high-speed moving cluster scene under on-chain data throughput and stability.

A device can retrieve data representing a plurality of activity sequences associated with a plurality of channels. Each activity sequence can include a plurality of activity entries having data values for a plurality of fields. The plurality of activity entries can be associated with respective timestamps. The plurality of activity sequences can have respective temporal resolutions. The device can flatten the data values of the plurality of activity sequences into a single time-ordered activity sequence across the plurality of activity entries, the plurality of fields, and the plurality of channels. The device can generate an activity data embedding using the single time-ordered activity sequence, generate an encoder output based on the activity data embedding and temporal information based on the respective timestamps using an encoder module, input the encoder output into a decoder module, and generate a decoder output based on the encoder output using the decoder module.

The invention relates to a system (100) for optimizing the configuration of crash tests and simulations for vehicle development. The system (100) comprises a data preparation module (200) that splits a data set (210) containing crash test and simulation data into a first training data set (210), a validation data set (230), and a test data set (240); a training module (300) with a first AI model (350) for creating configurations of physical crash tests and virtual simulations, wherein the first AI model (350) is trained with the first training data set (220); and a data value module (400) that calculates data values ​​(φ(i)) for the data points (i) of the crash test and simulation data of the training data set (220) with respect to the validation data set (230).a model optimization module (500) comprising a second AI model (550) and a training data generator (570), wherein the training data generator (570) creates a second training data set (580) which is used to train the second AI model (550) to predict the relationship between input parameters (p) and the computed data values ​​(φ(i)); a parameter module (700) which uses the trained second AI model (550) to find crash test parameters with a maximum data value (φ(i)).

A method comprising: processing an instruction to modify a trained artificial intelligence, AI, system, the AI system being configured to provide at least one output based on an input dataset, the trained AI system having the form of a tensor network, the instruction comprising adding a first dataset in the AI system and / or removing a second dataset from the AI system; and running the instruction on the trained AI system, which comprises: when the instruction at least comprises adding the first dataset, encoding data values of the first dataset in one or more tensors of the trained AI system associated with values of the first dataset; and when the instruction at least comprises removing the second dataset, setting to zero values associated with data values or relationships of the second dataset in one or more tensors of the trained AI system associated with values of the second dataset, or removing the one or more tensors associated with values of the second dataset from the AI system. Also, an apparatus, a system and a computer program associated with the method.

This application provides a health status monitoring method, system, device, electronic device, and storage medium, applied in the field of occupational safety and health monitoring technology. The method includes acquiring the fused data to be detected and physiological data observations of a target individual; inputting the fused data to be detected into a time series prediction model to obtain the predicted physiological data values ​​of the target individual, the time series prediction model being constructed based on a long short-term memory network; determining the health risk score of the target individual based on the predicted physiological data values ​​and the observed physiological data values; and issuing an alarm and protection measure if the health risk score exceeds a maximum score threshold. This application refines the process to the individual level, utilizing deep learning algorithms to accurately predict the health status of a target individual based on their physiological data and fused data, quantitatively assessing the individual's health risk, promptly detecting health abnormalities, and taking corresponding early warning and protection measures to reduce the occurrence of heat-related diseases and accidents in high-temperature environments, thus ensuring personnel safety.

This invention provides an intelligent safety management method and system for boiler walkway gratings, relating to the field of industrial safety technology. The method includes: S1, acquiring in real-time the obstruction signal sequence generated by an infrared beam sensor deployed at the grating inlet and the weight signal sequence generated by a pressure sensor deployed below the grating, and synchronizing the obstruction and weight signal sequences with timestamps; S2, inputting the synchronized obstruction and weight signal sequences into a pre-constructed lightweight spatiotemporal feature extraction network to extract multi-dimensional temporal features representing personnel flow, object presence, and weight distribution; and inputting these multi-dimensional temporal features into a risk fusion inference engine built based on Dempster-Shafer evidence theory. This system can eliminate perceptual ambiguity, overcome decision-making rigidity, and mine data value in the harsh edge environment of boiler walkways, achieving progressive intelligent safety management from precise risk identification to dynamic and flexible assessment and early hazard insight.

Apparatuses, systems, and techniques are to transfer data based, at least in part, on a computational graph. In at least one embodiment, a processor causes a compiler to generate instructions to prefetch one or more data values from dynamic random access memory (DRAM) into an in-processor cache based, at least in part, on a computational graph.

This invention discloses a method for real-time monitoring and offline correction of wind tunnel pressure test data. The aim is to solve a series of problems encountered during pressure testing, such as the inability to monitor the operating status of the pressure acquisition system, the inability to compare unknown data values, and the difficulty in determining the quality of test data. Without adding peripheral equipment, this invention fully utilizes the potential of existing pressure acquisition system equipment to achieve real-time dynamic monitoring of pressure data and provides a basis for offline data analysis and correction. Through analogy comparison, real-time monitoring of the operating status of the pressure acquisition system is achieved, reducing the risks of test run scrapping and data invalidation due to equipment failure. This invention requires minimal system modifications, is flexible and convenient to operate, and is economical and practical. The difference between the synchronously acquired set constant pressure and the measured constant pressure provides a basis for subsequent offline correction of the test data, improving data accuracy.

This invention provides a method and system for aggregating and storing water management control data based on edge acquisition, relating to the field of data processing technology. The method includes: deploying edge acquisition terminals to collect multi-source water management control data; performing quality cleaning to obtain standardized water management control data; performing real-time event detection and feature value extraction on the standardized water management control data at the edge side to generate target water management control data; based on the target water management control data and network perception, executing local reliable caching, online sending, and breakpoint resumption control according to preset priorities to obtain a data reporting stream; establishing a hierarchical message buffer and asynchronous decoupling channel on the central platform to persistently access and aggregate the data reporting stream to obtain a data aggregation stream; performing fine-grained classification and hierarchical storage processing on the data aggregation stream to obtain traceable hierarchical storage results; and providing a unified data service interface for the traceable hierarchical storage results to support on-demand subscription and distribution, completing the data value closed loop.

A method for dependency task prioritization is disclosed. The method includes providing base data including task identifiers, failure values, and dependency data values, where each dependency data value is associated with a pair of tasks. The method also includes generating a probabilistic model using a directed acyclic graph, where each task is associated with a network node and each dependency data value is associated with a network edge of the directed acyclic graph, where each dependency data value represents a conditional probability related to a respective per-time-unit failure rate. Additionally, the method includes determining, for each task in the directed acyclic graph, a posterior marginal probability value representing a probability of the task experiencing a failure, and selecting, based on the posterior marginal probability values, a sequence of tasks that are most likely to fail the fastest.

The application relates to a special variable user load feature extraction method, device, equipment and medium based on multi-dimensional time sequence data. The method comprises the following steps: preprocessing an original data set collected to obtain a reference data set, obtaining a to-be-repaired data point in the reference data set, respectively obtaining a spatial repair value and a time repair value of the to-be-repaired data point, fusing the spatial repair value and the time repair value based on a fusion weight to obtain a data repair value, updating a data value corresponding to the to-be-repaired data to the data repair value to obtain a repaired data set, performing time sequence alignment on a load repaired data set and an environment repaired data set to obtain a multi-dimensional time sequence data set, extracting a time sequence feature set of the multi-dimensional time sequence data set, screening the time sequence feature set to obtain a target feature set, and constructing a special variable user load space-time feature sample library based on the target feature set. The method can improve data processing precision.

This application relates to a cloud-native resource description framework (RPF) data storage system, method, and computer device. The system includes: a storage layer for storing triples sharing the same attribute in RPF graph data as a subgraph and storing them in cloud object storage, constructing a range-aware offset index for each subgraph; and a computation layer for receiving RPF queries, decomposing the RPF queries into multiple subqueries according to attributes, querying the range-aware offset index, obtaining the byte offset of the target data value in each subquery in the corresponding subgraph, and, based on a query processing efficiency model, determining a target access method for each subquery from multiple preset data access methods according to the byte offset, executing the target access method to output the subquery result, and concatenating the results of each subquery to generate the query answer. Using this system can significantly reduce storage and query operating costs while maintaining competitive query performance.

The present invention relates to a method for operating a system for processing multiple containers, the method comprising the steps of: - providing at least one container having an identification device by means of which the container can be uniquely identified, wherein an identifier can be paired with the identification device, the identifier being stored in a storage device connected at least temporarily to or capable of being connected to the system via a public network for data transmission; - processing the container using the processing equipment of the system; - collecting at least one data value relative to the container and / or relative to at least one processing step of the container; and - providing the at least one data value for transmission and / or storage in the storage device.

A method for caching memory comprising caching two data values, each of one of two ranges of application memory addresses, each associated with one of a set of threads, by: organizing a plurality of sequences of consecutive address sub-ranges in an interleaved sequence of address sub-ranges by alternately selecting, for each thread in an identified order of threads, a next sub-range in the respective sequence of sub-ranges associated therewith; generating a mapping of the interleaved sequence of sub-ranges to a range of physical memory addresses in order of the interleaved sequence of sub-ranges; and when a thread accesses an application memory address of the respective range of application addresses associated thereof: computing a target address according to the mapping using the application address; and storing the two data values in one cache-line of a plurality of cache-lines of a cache by accessing the physical memory area using the target address.

Memory devices and operating methods are disclosed. In an embodiment, a memory device may include a memory cell array including a plurality of memory cells, each of the plurality of memory cells configured to store a data value corresponding to read data to be read out through a plurality of conductive lines, and a read circuit connected to the plurality of conductive to generate the read data corresponding to the data value stored in a selected memory cell among the plurality of memory cells based on or according to whether there is a change in a cell current flowing through the selected memory cell during a single read period.

This invention discloses a computing power multiplication pre-storage system, method, and embedded device, belonging to the field of computing architecture and data reuse technology. Addressing the problems of redundant repetitive computation, conflict risks and irreparable damage in data integrity verification, and inefficient request-response modes in existing technologies, this invention proposes a closed-loop "pre-storage-reuse-verification" system. The system includes: a hotspot identification and adaptive pre-storage module, used to identify high-frequency computing tasks, dynamically adjust the pre-storage range, and automatically eliminate low-frequency data, achieving self-evolution and convergence of the data set; a multi-level trusted caching module, adopting a layered storage architecture to achieve layered management of data value, and possessing automatic backfilling between layers, periodic consistency verification, and automatic repair mechanisms; a mathematically based integrity verification module, configuring corresponding differential or recursive verification logic for a wide range of computing tasks, from basic data types and various mathematical functions to operational operators, providing a zero-conflict, reversible, and repairable lightweight data verification and restoration method; and an asynchronous push processing engine, which immediately returns after receiving a request, submitting the computing task to a background lock-free queue for batch processing, achieving decoupling between computation and requests. This invention pioneers the deep integration of differential verification and computation acceleration, reconstructing the traditional "request-computation-response" logic into a "pre-store-query-retrieve" push-pull interaction logic. By reusing repeated calculations through module collaboration, it not only significantly reduces computation latency, but more importantly, it improves the effective utilization of computing power, greatly saves hardware resources and energy consumption, and ensures data credibility and integrity. It is applicable to fields such as artificial intelligence, scientific computing, engineering simulation, financial technology, and video processing.

The application relates to the technical field of data storage, and discloses a storage layering method for data storage and data disaster recovery, which comprises the following steps: calculating a medium fatigue index by monitoring the physical health state of a bottom-layer storage medium in real time, and calculating a data reconstruction entropy in combination with data sources and information entropy; selecting a physical layout strategy according to the two-dimensional mapping results of the two, wherein the strategy comprises a sentinel interleaving distribution strategy and a write mode polymorphic conversion strategy. The former uses low-value sentinel data to surround core data at the physical layer to perceive medium deterioration in advance and trigger migration, and the latter reduces medium wear by aggregating random writing. In the disaster recovery synchronization stage, the transmission priority is dynamically adjusted according to the medium fatigue risk, and the decoupled transmission of metadata and load and the anchor recovery are performed. The application realizes differentiated protection based on the difference between the medium physical state and the data value, and effectively improves the survival probability of key data in the medium aging period and the disaster recovery efficiency.

This invention discloses a method, device, and computer-readable storage medium for improving frame rate in game scenes. The method includes: identifying whether each element color value in the first element color data value set of the main scene model in the main buffer of the current frame is identical to an element color value in the second element color data value set of the simplified model in the secondary buffer; in the next frame, placing each element with the same element color value in the secondary buffer and waiting directly for image rendering; performing coordinate transformation, perspective transformation, and cropping operations on each element with different element color values, placing it in the main buffer, and waiting for image rendering. This achieves an efficient game scene frame rate improvement scheme, reduces computational load, saves processing resources, and enhances the user's gaming experience.

A system and method for identifying data connections may submit alert data items of one or more datasets to a machine learning model, wherein the alert data items of each dataset include: an alert rule that initiated an alert for the dataset including a first set of thresholds, one or more data values assessed by the first set of thresholds in the generation of the alert, and an alert categorization of the alert selected from a true positive categorization or a false positive categorization; assess, combinations of the alert categorization in relation to the one or more data values and the alert rule; generate a second set of thresholds for the one or more data values, wherein the second set of thresholds has a reduced false positive categorization of the alerts compared to the first set of thresholds; and update the alert rule to comprise the second set of thresholds.

A method (100) and a device for the semi-automated creation of digital map content are presented, comprising: - Reading (110) the digital map; - Receiving (120) environmental data values ​​representing the environment of at least one vehicle; - Automated generation (130) of initial map content from the received environmental data values; - Verification (140) of the initial map content; - Confirmation (150) or adjustment (151) of the initial map content; - Automated calculation (160) of secondary, validated map content using the verified and validated or adjusted initial map content with validated algorithms; - Insertion (170) of the secondary, validated map content into the digital map; and - Provision (180) of the digital map.