14 results about "Metadata element" patented technology

Techniques for processing sensor data are provided. Sensor data, such as individual messages or data points from devices having one or more hardware sensors, can be annotated with one or more metadata elements to facilitate sensor data processing. An annotation rule for sensor data can be determined and sensor data annotated according to the annotation rule. Sensor data can be written to a relational database table, where the table has a schema that provides columns for storing data for particular indicators of an indicator group having a plurality of indicators.

Visual representations represented in computer files can undergo various changes, in terms of specific visual details in a visual representation, without changing the semantics of what is represented. The present disclosure provides techniques and solutions for generating an identifier for a visual representation using one or more content-independent semantic metadata elements. Content-independent semantic properties are those that do not correspond to individual visual elements in a visual representation, or to properties of a visual representation that do not contribute to a description of an overall semantic provided by the visual representation. Disclosed techniques can be used to identify when a visual representation is generated or imported that has the same overall semantic, as indicated by the identifier, as another visual representation. The two visual representations can have the same or different image elements. Disclosed techniques also provide that visual representations that have a different overall semantic are assigned different identifiers.

Techniques and solutions for storing and processing metadata are described. A target system sends a request to a source system to identify extensions to one or more specified database artifacts. The source system identifies one or more software objects that include metadata extensions to the one or more specified database artifacts, and in response to the request, sends at least a portion of such metadata elements to the target system. The source system can expose an API, such as an API in a standard format, to the target system to facilitate requesting and retrieving metadata from the source system.

The invention provides an automatic metadata recognition and extraction method for remote sensing images and spatial data, and belongs to the technical field of remote sensing measurement. Multi-source remote sensing image data are collected and preprocessed to establish a multi-modal image set under a unified geographic coordinate system, and an image pyramid is constructed by using a GPU accelerated block parallel processing architecture; a topographic feature extraction algorithm based on topology durability is used to identify stable topographic markers, a geometric registration feature extraction and matching network is constructed, a structured prediction framework based on a probability graph model is used to carry out accurate registration, and adaptive filtering and multi-modal data fusion are carried out on a registered image set. A semi-supervised classification algorithm based on random walk is used for carrying out ground feature classification, metadata elements are automatically identified according to a ground feature classification result and stable topographic markers, and the technical problem that the registration precision is insufficient due to the fact that topographic feature extraction is prone to noise interference in multi-mode remote sensing image registration is solved.

A system and method for multi-level compaction of floating-point numbers and associated metadata within datasets. The system identifies floating-point numbers and their associated metadata, pre-encodes numbers into binary string representations, and encodes metadata into compact binary form. These encoded elements are linked together and indexed to indicate they represent floating-point numbers with metadata. The dataset is organized into multiple compaction levels based on semantic relationships between metadata elements. The system creates specialized indices for metadata-based retrieval, maintains relationship maps, and implements inheritance policies across hierarchical levels. During retrieval, the system reconstructs both the original floating-point values and their associated metadata, preserving hierarchical relationships. This approach enables more intelligent data organization, richer contextual information preservation, and more powerful query capabilities while maintaining efficient floating-point compaction.

The invention discloses an archive management method and system based on metadata, electronic equipment and a storage medium, and the method comprises the steps: defining metadata of all archive types in an archive system, and constructing a unified metadata model; classifying the metadata, and extracting public metadata and private metadata; configuring basic information of the metadata; in a file configuration page, a metadata component is introduced in a dragging mode, a file entry form, a list and a detail page are constructed, and a corresponding database table structure is automatically generated; monitoring MySQL Binlog on the basis of Canal, collecting data of public metadata elements in the file table in real time, and synchronizing the data to Elasticsearch; a unified index is constructed based on Elasticsearch, and unified retrieval across file types is achieved. According to the method, the problems of difficulty in standard landing, poor expansibility, low retrieval efficiency and the like in an existing archive management system are solved.

Various embodiments of the present technology generally relate to systems and methods for optimizing resources within a customer data platform (CDP). In certain embodiments, a method may comprise operating a resource optimizer system to implement a CDP resource optimization process to remove obsolete metadata, the CDP resource optimization process including monitoring metadata usage within a CDP, generating metrics for a metadata element based on the metadata usage, defining a rule set for selecting the obsolete metadata for removal based on the metrics, and applying the rule set to remove the obsolete metadata.

The invention relates to the field of railway engineering, and discloses a railway engineering metadata updating and publishing method and device. Comprising the following steps: performing authority management based on a role access control model; node fragmentation is carried out according to projects, lines and professions, modifiers are distributed, and a metadata element relation tree and content are modified and submitted; an auditor audits the modification opinions, judges conflicts in combination with a semantic analysis method and a weight rule base and outputs an auditing result; a version number is given to the metadata unit passing the auditing, and the metadata unit is packaged to form a metadata packet; overall or staged release is carried out on the metadata packet, and gray release and A / B testing are supported; a digital signature and encryption mechanism is adopted in the publishing process, so that the integrity and security of the metadata in the transmission and storage process are guaranteed; therefore, the metadata updating and publishing efficiency is improved, the multi-specialty cooperation capability is enhanced, and the data security and credibility are improved.

An information processing device comprises a P-value calculation unit that calculates a module P-value for verifying whether a formed module is correct for a module configured from elements included in multivariate data for which correlation network analysis is to be performed.

This information processing device comprises: an FNI analysis unit that executes an FNI analysis process for incorporating a false negative element into each of a plurality of modules composed of elements possessed by multivariate data subjected to correlation network analysis; and an FNI assignment processing unit that executes an assignment process for eliminating duplication with respect to duplicating elements in the plurality of modules that are generated by the FNI analysis process.

When configuring a seed element module from non-seed elements having a higher correlation with a seed element among elements of multivariate data to be subjected to correlation network analysis, a program causes a computer to: execute, for individual ranks while increasing the ranks, an FPO analysis process for removing false-positive non-seed elements from the non-seed elements having the higher correlation with the seed element; store, in a storage unit, configuration information pertaining to the module on which the FPO analysis process has been executed; and stop the FPO analysis process and terminate a search for a module indicating a maximum module F score of the ranks early when a module identical to the configuration information of the module stored in the storage unit is constructed. The program causes the computer to execute an FNI analysis process for capturing false-negative elements, and, simultaneously with the FNI analysis process, causes the computer to calculate an element P value using a recursive formula while computing, for an element of interest, an element specificity rate at individual correlation rankings of a candidate element that is an element outside of the module.

A system to determine a context and likelihood of a vehicle hitting a guardrail is disclosed. The system is configured to detect, by sensors, where a vehicle hits a guardrail in one or more guardrail collision events; determine metadata elements associated with the one or more guardrail collision events; mapping the one or more guardrail collision events to a region into a vector format; determine, using a first trained machine learning model, a first likelihood if a given vehicle will hit a guardrail in the region on a given link at a given time based on the mapped guardrail collision events and a training feature dataset; and determine, using a second trained machine learning model, a second likelihood that the given vehicle will go over the guardrail into an unsafe area based on the first likelihood and guardrail collision features.

A computer-implemented method of backup and restore in a network data storage system is provided. The method includes generating, at a predefined time interval, a series of one or more virtual snapshots including, for each item in the network data storage system: (i) a strong hash of the item data, and (ii) one or more metadata elements related to the item. The method includes, in response to a request to restore a particular item: (i) searching the series of virtual snapshots for all available sources of the particular item, (ii) identifying the best source for the particular item, and (iii) recovering item data for the particular item from the identified best source.

A system for storing aggregated sensor data in a relational database, comprising: a storage facility; one or more processing units coupled to the memory; and one or more computer-readable storage media that store instructions which, when loaded into memory, cause one or more processing units to perform operations that include: by means of a data collection service (120, 312) periodically reading sensor data from a plurality of devices from a streaming service (114), wherein each device of the plurality of devices comprises one or more hardware sensors; Determining a set of attributes or metadata elements to be applied to the sensor data and annotating the sensor data by a tagging component to produce tagged data, wherein the annotation of the sensor data includes adding metadata to the sensor data or editing metadata of the sensor data, wherein the one or more hardware sensors are grouped into one or more indicator groups, and wherein the tagged data is stored as time series data in a data store; by an aggregation engine (356), aggregating data for a group by generating one or more aggregated values ​​from the tagged data stored in the data store; through an aggregation engine (356), writing the aggregated values ​​as aggregates in a semi-structured format back into data storage; and by a database writer (374), instantiating a relational database table, wherein the relational database table comprises for each respective hardware sensor in an indicator group a respective column in which aggregate values ​​for the respective hardware sensor are stored; and Calling a data read method to retrieve data for the aggregates and writing the aggregates to the relational database table.