30 results about "Prospective data" patented technology

A data flow is intercepted, the intercepted data including a set of data fields carrying a corresponding set of content. An intent is identified behind a transaction including the intercepted data. A conformity indication is set relative to a first data field in the set of data fields to indicate nonconformity of a first content of the first data field, the setting including comparing the first content with expected data corresponding to a mapping of the intent in a knowledge graph. Based on the conformity indication, the first content is modified to form modified content. In the transaction in the data flow, the first content is replaced with the modified content, the replacing forming a modified transaction. The modified transaction is transmitted to a receiver data processing system over a data integration channel.

Techniques for determining one or more expected categories of data for receipt by a skill or application and comparing the expected categories of data to user disclosed data, such as from a spoken natural language user input. The techniques include determining the spoken natural language user input is directed at an interaction with a particular skill and identifying a set of data categories registered for receipt by the skill. The techniques may further include determining if the skill solicited the disclosed data of the user input or if the user mistakenly provided the disclosed data. In some embodiments, the interaction with the skill may end if the skill is not authorized to receive the disclosed data. In some embodiments, the unsolicited disclosed data may be used to identify misunderstood or confusing requests for user input.

Systems and methods are disclosed for software security analysis. In certain embodiments, a method may comprise identifying a set of potential security vulnerabilities, comparing the potential vulnerabilities to a catalog identifying elements on a client system, and generating risk mitigation advice based on potential security vulnerabilities matching an element in the catalog. The method may include evaluating a data field of a service request to a third party to determine an expected data type for the field, determining whether the actual data included in the service request matches the expected data type, and quarantining the service request when the actual data does not match the expected data type. The method may comprise operating as a proxy for the service request, including receiving the service request from the client system, evaluating the service request for irregularities, and forwarding the service request to the third party once the irregularities have been addressed.

The invention relates to a regression test method and system for position information release and electronic equipment, and the method comprises the steps: obtaining a plurality of groups of test case data suitable for a target position based on a preset test case data set, the test case data comprising legal user identity data, test data and expected data; performing simulation release of target position information based on the test data of each test case; release response data of multiple dimensions are obtained, and verification is carried out based on the expected data of each test case in each dimension and the release response data; and recording data generated during simulation release of the target position information, release response data of multiple dimensions and verification data, and generating a regression test report for release of the target position information based on the recorded data. According to the invention, the test efficiency is improved, the manual labor amount is reduced, the test accuracy is high, the coverage is wide, and the expandability is high.

Systems and methods are disclosed related to triggering of data collection for User Equipment (UE)-side Artificial Intelligence (AI) / Machine Learning (ML) models. In one embodiment, a method performed by a UE for UE-side data collection for training, retraining, or fine tuning a UE-side AI / ML model comprises transmitting, to a network nod, information related to one or more UE-side conditions related to an expected quality of data samples that can be collected by the UE. The method further comprises receiving, from the network node, an indication to start data collection at the UE using a predefined, preconfigured, or indicated radio resource configuration or an indication to send a request to the network node for a radio resource configuration for data collection for training, retraining, or fine tuning the UE-side AI / ML model.

The invention relates to a time sequence data transmission method and device, equipment and a storage medium. The method comprises the following steps: in the process of receiving time sequence data sent by a sending end, extracting a data logic sequence number from data when receiving one piece of data; determining a data type corresponding to the data according to the data logic sequence number of the data; under the condition that the data type corresponding to the data is expected data, submitting the data to a preset processing unit; under the condition that the data type corresponding to the data is advanced data, storing the data into a buffer slot position corresponding to the data logic sequence number, and updating buffer slot position state data; data completion control is performed based on the buffer slot status data in order to attempt to complete missing data prior to the data. According to the method, dynamic classification, expected data submission and advanced data caching are performed on the data through the data logic sequence numbers, so that the cache resource occupancy rate can be effectively reduced, overall sorting is not needed in the whole process, and meanwhile, the data integrity can be guaranteed.

Methods and apparatus, including computer program products, are provided for processing analyte data. In some exemplary embodiments, there is provided a method. The method may include selecting at least one module from among a plurality of modules, the selection performed based on metadata including one or more of the following rules: whether the at least one module can be used with a type of device, whether the at least one module can be used with a glycemic state of a host, and whether the at least one module can be used with an expected volume of data generated by the type of device; and generating a report including the selected at least one module configured to present information representative of the glucose concentration level measured in the host. Related systems, methods, and articles of manufacture are also disclosed.

A system that includes the following: a processor; a storage facility; and a machine-readable memory that stores instructions, whereby the instructions can be executed by the processor to: to receive inputs (400) specifying an expected amount of data and a minimum retention period for a deduplication data store (150); to perform a comparison of the at least one retention period with a stored data structure (170), wherein the stored data structure (170) comprises different combinations of respective storage multipliers corresponding to the respective maximum retention periods; to determine at least one storage multiplier of the respective storage multipliers based on the comparison of at least one retention period with the stored data structure (170); to determine a storage quantity to be provided for the deduplication data store (150) based on the expected amount of data and the determined minimum storage multiplier; and to provide the deduplication data store (150) based at least on the specified amount of storage.

Systems, methods, and non-transitory machine-readable media for provisioning a deduplicated data store are provided. Example embodiments relate to provisioning a deduplicated data store. Examples include receiving input indicative of an expected data volume for a deduplicated data store and at least one retention period; performing a comparison of the at least one retention period to a stored data structure; determining at least one storage multiplier based on the comparison of the at least one retention period to the stored data structure; and determining a storage volume to provision for the deduplicated data store based on the expected data volume and the at least one storage multiplier.

Computing platforms, methods, and storage media for managing input data compatibility with a software application are disclosed. Exemplary implementations may: receive an input file having input data content arranged according to a first data format; compare the input data content with expected data content in relation to which the software application has been configured; compare the first data format with an expected data format in relation to which the software application has been configured; in response to determination that the input data content substantially overlaps with the expected data content and the first data format differs from the expected data format: generate a rearranged input file by rearranging the input data content according to the expected data format; and provide the rearranged input file to the software application for processing. Exemplary implementations avoid processing incompatibility and errors while avoiding the need to reconfigure the application.

A capability migration prediction method and system in industrial skill practical training relates to the field of occupational skill assessment, and the method comprises the following steps: firstly, obtaining a constraint condition type of virtual environment relative to real equipment simplification, and recording an operation performance difference value as constraint condition dependence intensity by setting a constraint-containing and unconstrained control group and experiment group virtual environment; then, analyzing constraint conditions related to each link of a real machine task, calculating single capability loss based on dependency intensity and a virtual-real difference multiple, and performing weighted summation by considering coupling coefficients among the constraint conditions to obtain a total capability loss predicted value; and finally, the predicted value is converted into real machine expected data, and a virtual-real ability migration evaluation result of the target student is generated by comparing the real machine expected data with actual data. By implementing the method, the refinement degree of virtual and real capability migration evaluation can be improved.

This specification discloses a resource allocation method, apparatus, and equipment. The scheme includes: identifying a resource allocation requester who holds a first resource and requires a second resource to supplement the first resource; identifying a resource holder who can provide the second resource and requires a third resource, wherein the third resource can be derived from the first and second resources; acquiring due diligence data related to the resource allocation requester and the resource holder; extracting a set of characteristic variables from the due diligence data, the set of characteristic variables including: a first subset of characteristic variables reflecting the resource holder's ability to provide the second resource; and a second subset of characteristic variables reflecting the resource allocation requester's ability to attract resources; generating risk measurement data for the first resource based on the first subset of characteristic variables; and generating derived expected data for the third resource based on the risk measurement data and the second subset of characteristic variables, so as to determine whether to allocate the second resource from the resource holder to the resource allocation requester based on the derived expected data.

Method of protecting integrity of data including steps of running web service on primary, secure computer system including original, complete data set created by user. Generating intended state of data of the web service on primary, secure computer system, so intended state of data has frontend data, files and information relevant for visual design and interaction of the web service. Transferring intended data set through secure connection to secondary computer system(s) in potentially insecure network on which the web service is executed. Checking integrity of intended data set by detecting manipulation of the underlying information of intended data by an attacker, after manipulation, manipulated data is placed in quarantine and may be analyzed in further step but is no longer executed and thus cannot cause any damage. Restoring intended state of data at time before manipulation by transferring intended data set stored on primary computer system to secondary computer system(s), so manipulation of data has been detected.

The invention relates to the technical field of memory testing, and discloses a memory testing tool, a memory testing analysis method thereof and a storage medium, and the memory testing analysis method comprises the following steps: before executing each testing step, according to the address generation logic of the memory testing tool, determining a target memory address to be accessed in the current testing step, determining an operated memory area of the current test step based on the target memory address; before the current test step is executed, actual data of the operated memory area are read to serve as original data before operation, and corresponding expected data are generated based on the original data and the test mode of the current test step; after the current testing step is completed, actual data of the operated memory area are read and serve as actually measured data after operation; and combining the original data, the measured data and the expected data into a data recording unit of the current test step, and sequentially storing the data recording unit according to a time sequence of test execution to form a data frame sequence organized according to a test process.

This invention discloses a self-governing method for VOCs quality control, belonging to the field of VOCs governance technology. The method includes: setting up a VOCs information model for users; improving the VOCs monitoring system based on the VOCs information model; conducting real-time monitoring through the VOCs monitoring system to obtain VOCs monitoring data; matching applicable measures from a preset measure library based on the VOCs information model; performing governance simulation based on the applicable measures and the VOCs information model to obtain simulated governance expected data; displaying the simulated governance expected data in the VOCs information model; acquiring governance needs in real time; analyzing the governance needs based on the VOCs information model; and determining the recommended governance method to meet the governance needs. This invention not only solves the self-governing VOCs quality control problem of a single enterprise, but also achieves data interoperability, resource collaboration, and intelligent decision-making for multiple users by constructing a regional / industry-level comprehensive VOCs governance platform.

The application relates to the technical field of data processing, in particular to a data desensitization method and system capable of keeping expected data characteristics, which comprises the following steps: firstly, determining a key data column and a characteristic set of an original data set; secondly, performing standardization processing on the original data set; thirdly, dividing the original data set into a plurality of data clusters with similar characteristics by using a clustering analysis technology; fourthly, replacing data points in the data clusters; fifthly, calculating characteristic differences between the original data set and a desensitized data set; and finally, performing k-anonymity and l-diversity tests on the desensitized data set. While ensuring data privacy security, the application effectively keeps key characteristics of the original data, significantly improves the usability of the desensitized data, accurately controls desensitization intensity through a dynamic clustering and characteristic weighting mechanism, avoids data distortion problems caused by excessive desensitization in traditional methods, and ensures that the data meets strict privacy protection requirements through the k-anonymity and l-diversity tests.

A computer-implemented system and method can be used to identify policy information applicable to a compute resource within a specified time range, the policy information related to data management for the compute resource. Based on the identified policy information, a set of expected data management events for the compute resource is generated within the specified time range. The set of expected data protection events is modified based on information related to exceptions to the data management indicated by the policy information. The modified set of data protection events provides lineage information for the compute resource.

This invention discloses a SCADA incident inversion method, apparatus, equipment, and medium, relating to the field of monitoring technology. The method includes: determining an inversion time interval based on an alarm event and a preset inversion duration; acquiring historical data within the inversion time interval, and processing unexpected or missing data using a preset data repair strategy to obtain a continuous time-series target historical data sequence; based on the target historical data sequence, and combining the correlation between historical data and SCADA screen configuration, reconstructing and rendering the monitoring screen state at the target time according to a set time step, generating time-series image frames; and synthesizing the time-series image frames into an incident inversion playback video. This enables intuitive restoration and controllable playback of the incident process within a specified time period of the SCADA system, making the incident inversion process more intuitive and visual, while also possessing video-level playback control capabilities, effectively improving the efficiency and intuitiveness of incident analysis.

A computer-implemented system and method can be used to identify policy information applicable to a compute resource within a specified time range, the policy information related to data management for the compute resource. Based on the identified policy information, a set of expected data management events for the compute resource is generated within the specified time range. The set of expected data protection events is modified based on information related to exceptions to the data management indicated by the policy information. The modified set of data protection events provides lineage information for the compute resource.

The application discloses a data collection integrity detection and packet loss positioning method and system based on M sequence, relates to the technical field of data collection and processing, and is characterized in that M sequence generators with the same initial state and polynomial are arranged at the sending end and the receiving end, the receiving end compares a data packet sequence number extracted from a data packet with an expected data packet sequence number, judges whether the two sequence numbers match, if the two sequence numbers match, the state of the M sequence generator at the receiving end is advanced by one step, and the expected data packet sequence number is stored in a received sequence number database, and if the two sequence numbers do not match, a sequence number difference is calculated according to the extracted data packet sequence number and the expected data packet sequence number, data packet integrity transmission detection is performed according to the sequence number difference, and according to a detection result and log information of the sending end, a fault cause is positioned and a recovery strategy is performed. The application realizes self-synchronization based on the determinacy principle of M sequence, thereby realizing multiple error detection at low cost.

The invention discloses a VOCs quality control autonomous method, and belongs to the technical field of VOCs governance, the method comprises the following steps: setting a VOCs information model for a user, and perfecting a VOCs monitoring system according to the VOCs information model; real-time monitoring is carried out through the VOCs monitoring system, and VOCs monitoring data are obtained; matching applicable measures from a preset measure library according to the VOCs information model; performing treatment simulation according to the applicable measures and the VOCs information model to obtain simulation treatment expected data; displaying in the VOCs information model according to the simulation treatment expected data; acquiring a treatment demand in real time, analyzing the treatment demand based on the VOCs information model, and determining a treatment recommendation mode meeting the treatment demand; according to the system and the method, the VOCs quality control self-governance problem of a single enterprise is solved, and data intercommunication, resource collaboration and intelligent decision of multiple users are realized by constructing a region-level / industry-level VOCs comprehensive treatment platform.

The invention belongs to the technical field of big data, and particularly discloses a data synchronization system and method from a PostgreSQL database to an ElasticSearch index.The method comprises the steps that firstly, an ID interval is divided in a synchronization control module, then a synchronization instruction is sent to a data transmission module according to the divided ID interval, the data transmission module reads a target ID interval and calls a verification module to calculate the expected data size, and the expected data size is sent to the data transmission module; the data transmission module writes the data into the ElasticSearch index, the verification module judges whether the actually written data volume contains all IDs in the interval, if the verification is passed, the synchronization control module records a synchronization success log, and if the verification is not passed, the synchronization control module triggers the retry module to perform retry. The problems that an existing scheme cannot meet the requirements of integrity verification, low resource consumption and adaptive service scenes are solved. According to the invention, a dual verification mechanism of ID interval coverage and data volume matching is adopted, so that misjudgment of ID verification is avoided.

A program command specifying new data to be programmed is received and partitioned into a plurality of data partitions. A wordline addressing a first set of memory cells to be programmed with a data partition of the plurality of data partitions is identified for a specified block of the memory device. Existing data stored by a second set of memory cells is read. An expected data state metrics is produced for each data partition of the plurality of data partitions. A data partition associated with a lowest expected data state metric among the plurality of expected data state metrics is identified. The identified data partition is programmed to the identified wordline.

The exemplary system is for testing a device under test (DUT) comprising a first core and a second core. The system includes parallel channels for connecting to several pins on the DUT. The channels are for transmitting test data to the DUT and for receiving measurement data from the DUT based on the test data. The measurement data includes time-division multiplexing (TDM) data consisting of sequential data packets received from the DUT via the channels as part of a bitstream. Each data packet includes a first number of bits from the first core and a second number of bits from the second core. The circuit configuration associated with the channels is configured to compare the measurement data with expected data and to determine a pass / fail status for the first and second cores based on the comparison.

Techniques for determining one or more expected categories of data for receipt by a skill or application and comparing the expected categories of data to user disclosed data, such as from a spoken natural language user input. The techniques include determining the spoken natural language user input is directed at an interaction with a particular skill and identifying a set of data categories registered for receipt by the skill. The techniques may further include determining if the skill solicited the disclosed data of the user input or if the user mistakenly provided the disclosed data. In some embodiments, the interaction with the skill may end if the skill is not authorized to receive the disclosed data. In some embodiments, the unsolicited disclosed data may be used to identify misunderstood or confusing requests for user input.

The invention discloses a dynamic anti-vibration and heat management integration method for a vehicle-mounted energy storage system based on road condition prediction. The method comprises the steps that a prospective event sequence containing at least one future disturbance event is generated based on prospective data obtained from at least one vehicle-mounted data source, and the future disturbance event comprises predicted occurrence time and intensity level; based on the prospective event sequence, generating an integrated pre-response control time sequence instruction for cooperatively regulating and controlling a dynamic anti-vibration system and a thermal management system of the energy storage system; and controlling the dynamic anti-vibration system and the thermal management system to execute a pre-response adjustment action at an execution moment indicated by the pre-response control time sequence instruction. Through a feedforward control mechanism, the response delay and the thermal lag of a traditional control strategy are eliminated, the mechanical stability and the thermal stability of the energy storage system can be synergistically and foreseeably optimized, and the operation safety, the reliability and the comprehensive energy efficiency of the system are remarkably improved.

This invention relates to the field of information acquisition technology and discloses an electronic information acquisition system based on a wireless communication network. The system includes a task semantic deconstruction module, a dynamic instance evaluation module, a semantic pipeline negotiation module, a knowledge graph construction module, a multi-dimensional verification and repair module, and a data encapsulation and caching module. First, the task description file of the acquisition target is deconstructed to obtain the data semantic description and expected data features. Then, based on this, candidate data source instances are obtained and their health scores are given, adapted to the dynamic network environment. Next, a standardized data acquisition pipeline is negotiated based on the scores, and a knowledge graph is constructed based on the pipeline and expected features to obtain semantic intermediate data. Subsequently, multi-dimensional verification and repair are performed on this data to form qualified intermediate data. Finally, the data is encapsulated according to a preset specification to obtain the target acquisition dataset and cached in a designated location. This invention can improve the efficiency of electronic information acquisition.

A power tool system includes a hydraulic power tool. The hydraulic power tool includes a hydraulic drive, a sensor, and a first electronic processor. The sensor is configured to detect an operational parameter of the hydraulic drive during an operation by the hydraulic drive. The first electronic processor is configured to store a plurality of data points based on the operational parameter detected during the operation and send the plurality of data points to an external device. The external device includes a display screen and a second electronic processor configured to receive the plurality of data points from the hydraulic power tool, control the display screen to display an expected data point for the operational parameter for the operation, and control the display screen to display an actual data curve based on the plurality of data points, the actual data curve overlaid on the expected data point.

This invention discloses a system performance inspection method, apparatus, device, medium, and product, relating to the field of performance testing technology. The method includes: determining target test cases for the system under test based on data information, at least two sub-functional information, and the test requirements of the system under test; running the target test cases in the system under test to obtain execution data; and determining the performance test results of the system under test based on the execution data and the expected data of the target test cases. This invention can efficiently and comprehensively determine target test cases for pre-deployment inspection of the system under test based on the test requirements, data information, and at least two sub-functional information. The target test cases are then used to automatically inspect the system under test, ensuring the quality of system testing, improving testing efficiency, and reducing inspection costs.

A data flow is intercepted, the intercepted data including a set of data fields carrying a corresponding set of content. An intent is identified behind a transaction including the intercepted data. A conformity indication is set relative to a first data field in the set of data fields to indicate nonconformity of a first content of the first data field, the setting including comparing the first content with expected data corresponding to a mapping of the intent in a knowledge graph. Based on the conformity indication, the first content is modified to form modified content. In the transaction in the data flow, the first content is replaced with the modified content, the replacing forming a modified transaction. The modified transaction is transmitted to a receiver data processing system over a data integration channel.