123 results about "DataFlash" patented technology

The invention provides a financial statement generation method and system based on cloud computing, and the method comprises the steps: collecting multi-source data of an internal business system of an enterprise through a centralized data integration platform based on a cloud computing environment, carrying out the classified storage, and constructing a data set; verifying the data set, and obtaining key index fields related to financial statement generation in the verified data set; performing grouping calculation on the key index fields by adopting a data aggregation algorithm to form a financial data summarization result; dynamically mapping the financial data summarization result by adopting a report generation engine, and matching with a preset financial report template to obtain a report data framework; and performing secondary verification and encryption on the report data framework to obtain a final financial report. According to the technical scheme, automation, real-time performance and unmanned performance of financial statement generation are realized through full-link innovation of edge intelligent acquisition, streaming processing, incremental aggregation and zero-trust security.

A data pipeline validation system and method configured to partially automate testing of data pipelines in a distributed computing environment. The system includes a data pipeline analytic device equipped with various modules, such as a query generation module, data frame comparison module, and metadata management module. The query generation module employs natural language processing techniques to analyze configuration entries and dynamically generate SQL queries tailored to specific test cases. The data frame comparison module compares the results of different test cases using distributed collections, enabling parallel processing and efficient result comparison. The metadata management module captures and stores relevant metadata for traceability and auditing purposes. The system facilitates comprehensive validation of data pipelines, enabling organizations to ensure the accuracy, reliability, and integrity of data.

Systems and methods are described for batch materialization of an incremental change data capture (CDC) changeset with full row changes. The primary keys are extracted from the incremental CDC changeset and an indication of the extracted primary keys are broadcast to a plurality of executors. The primary keys may be added to Bloom filter or a plurality of Bloom filters that are broadcast to the executors. Each executor filters a baseline data table based on the extracted primary keys to generate a baseline match dataframe with all primary keys matching the extracted primary keys, and a baseline unmatched dataframe with all primary keys not matching the extracted primary keys. Each executor receives full row changes from a partitioned incremental CDC changeset and combines the changes with the baseline unmatched dataframe to produce a final changed baseline data table.

The invention belongs to the technical field of security monitoring, and particularly relates to a multi-sensor fusion security monitoring method and system, which realizes time alignment of data by starting a data synchronization process and dynamically adjusting the data flow rate of each sensor, and effectively solves the real-time challenge caused by the time delay difference of the sensor data. According to the method, the real-time performance of the system and the consistency of data processing are improved, the consistency and reliability of data are enhanced by constructing a unified data framework and executing an exception detection process, and the situations of data loss and inconsistency are reduced; besides, anomaly detection is carried out by utilizing a unified data framework, potential risks can be identified more accurately, and corresponding early warning signals are activated in time, so that the early warning response capability of the system is optimized; in conclusion, the overall performance and reliability of the multi-sensor fusion safety monitoring system are remarkably improved.

A method includes a processing module obtaining touch data at a touch data rate. The method further includes the processing module obtaining video data at a refresh rate, wherein the touch data rate is greater than the refresh rate. For a frame of the video data, the method further includes the processing module determining a touch movement trend based on the touch data. The method further includes the processing module determining a position offset for a graphical representation of the touch data based on the touch movement trend. When the position offset exceeds an offset threshold, the method further includes the processing module adjusting position of the graphical representation of the touch data within the frame of video data based on the position offset to produce an adjusted frame of video data.

The present application discloses a method, system, and computer system for providing a dataframe as a service. The method includes (a) receiving, from a client system, one or more hints identifying parameters for source data; (b) executing a plan for a source dataframe including determining whether accessing the source data for the source dataframe is permitted based at least in part on one or more security policies, wherein the plan is based at least in part on the one or more hints; (c) receiving from the client system a business logic pertaining to a transformation to be applied to the source dataframe; and (d) providing to the client system information pertaining to an execution result obtained based at least in part on the business logic.

The present disclosure relates to systems, methods, and devices for providing a centralized data store that receives and transmits data via agents that operate independently of one another. In some implementations, the agents transform data prior to transmission to the centralized data store. In some implementations, the centralized data store is configured to transform data. The centralized data store can evaluate, route, score, and otherwise manipulate and select received data. The centralized data store can respond to data requests based at least in part on its evaluation of received data.

A method for managing a plurality of imaging devices in a vehicle includes determining that a change of data security mode is indicated for frames of image data transmitted over a first data communication link, determining whether a sensor management system has sufficient processing capacity to support the change of data security mode, increasing the processing capacity of the sensor management system by modifying data security settings for at least one other data communication link when the processing capacity of the sensor management system is insufficient to support the change of data security mode, and initiating the change of data security mode when the sensor management system has sufficient processing capacity to support the change of data security mode. The change of data security mode may include a change from an application-based to a link-based data security mode or a change from the link-based to the application-based data security mode.

Systems and methods are described for batch materialization of an incremental change data capture (CDC) changeset. The primary keys are extracted from the incremental CDC changeset and an indication of the extracted primary keys are broadcast to a plurality of executors. The primary keys may be added to Bloom filter or a plurality of Bloom filters that are broadcast to the executors. Each executor filters a baseline data table based on the extracted primary keys to generate a baseline match dataframe with all primary keys matching the extracted primary keys, and a baseline unmatched dataframe with all primary keys not matching the extracted primary keys. Each executor receives a partitioned incremental CDC changeset and combines the changes with the baseline match dataframe to produce a final changed baseline data table.

A decoding method, a memory storage device, and a memory control circuit unit are provided. The decoding method is described below. A read command sequence is transmitted, the read command sequence instructs to read a first physical unit, and the first physical unit belongs to a physical unit group. A first single-frame decoding is performed on a first data frame read from the first physical unit. First error evaluation information corresponding to the physical unit group is obtained in response to the first single-frame decoding being failed and a default condition not being satisfied. This default condition is used for triggering the multi-frame decoding on the physical unit group. A second single-frame decoding is performed on the first data frame according to the first error evaluation information.

The application discloses a kind of security startup methods based on HSM security hardware support, including self-update step and security startup step: the code of Bootloader is copied a copy and repartition locates code to the code interval used by App, retains the erasing code flash function, and the main core and HSM interaction part are deleted, and it is called Bootloader2 carrying code;Boot manager module is added in the startup code in Bootloader, and the Bootloader code that needs to be re-burned into ECU after repair is compiled to generate hex, the hex file is set to refresh file with specified address, and self-update refresh file is obtained by merging;Bootloader2 and updated Bootloader' are formed;ECU receives the refresh instruction issued by refresh tool, writes App valid flag to CODE FLASH, simultaneously obtains hash1, stores hash1 in the special DataFlash of HSM, judges App valid, then calls HSM to calculate hash and obtains hash2, compares by reading hash1 through HSM, consistent, then runs App, otherwise, stay in Bootloader and only retain refresh function, protect against software attack of hacker, and can safely upgrade Bootloader and App code.

1. Name of the Design Product: Graphical User Interface for Editing Tabular Data of an Electronic Device. 2. Use of the Design Product: For an electronic device. 3. Design Key Points of the Design Product: Lies in the graphical user interface. 4. Picture or Photograph that Best Illustrates the Design Key Points: Front View. 5. The electronic device is of conventional design, and the rear view, left view, right view, top view and bottom view are omitted. 6. Use of the Graphical User Interface: The graphical user interface is used to edit and process data in a table through various judgment conditions, complex variables or functions. 7. Human - Machine Interaction Method of the Graphical User Interface: The graphical user interface can interact by clicking, pressing or swiping on the graphical user interface. 8. Description of the Changing States of the Graphical User Interface: The front view is a visual development platform. The left - hand list shows components of various functions. When a component is dragged with the mouse and placed in the blank area, the editing interface of the component will be displayed. For example, click the data table button in the main view to enter the change status diagram 1; click the edit button at the table data editing area in the change status 1 to enter the change status diagram 2; click the "Please select" button on the far left in the change status diagram 2 to enter the change status diagram 3; when clicking any one of the judgment conditions in the change status diagram 3, enter the change status diagram 4; when clicking the second "Please select" button on the left in the change status diagram 4, enter the change status diagram 5; when clicking any variable option button such as a function in the change status diagram 5, enter the change status diagram 6; click the edit function button in the change status diagram 6 to enter the change status diagram 7; click the OK button in the change status diagram 7 to enter the change status diagram 8; click the second button on the right in the change status diagram 8 to enter the change status diagram 9; click any judgment condition button such as ">= " in the change status diagram 9 to enter the change status diagram 10; click the add sibling button in the change status diagram 10 to enter the change status diagram 11. Similar to the operations in the change status diagrams 4 and 5, after selecting the judgment condition and variable type, enter the change status diagram 12. Enter specific content, such as X1, in the third data box from the left in the change status diagram 12; click the add child button in the second row of the change status diagram 12 to enter the change status diagram 13. Similar to the operations in the change status diagrams 4 and 5, after selecting the judgment condition and variable type, enter the change status diagram 14. Enter specific content, such as X1-1, in the third data box from the left in the change status diagram 14; click the add child button in the third row of the change status diagram 14 to enter the change status diagram 15. Similar to the operations in the change status diagrams 4 and 5, after selecting the judgment condition and variable type, enter the change status diagram 16. Enter specific content, such as X2, in the third data box from the left in the change status diagram 16; when clicking the first delete button from top to bottom in the change status diagram 16, enter the change status diagram 17; when clicking the OK button in the change status diagram 17, enter the change status diagram 18.

Embodiments of this application describe a communication method, a first station (STA), a second STA, and an access point (AP). One example method includes: determining, by a first STA, a first basic service set (BSS) color; generating, by the first STA, a data frame when the first station STA and a second STA perform D2D transmission, where the data frame includes the first BSS color; and sending, by the first STA, the data frame to the second STA.

The application discloses a kind of based on the post-investment risk early warning and exit decision auxiliary method and system of private equity investment project of stream data processing, belong to artificial intelligence and financial technology field.This method accesses multiple-source heterogeneous post-investment data in real time through distributed stream data framework, extracts static, dynamic and event trigger features after preprocessing using sliding window mechanism;Risk scoring fusion is carried out based on time series anomaly detection and gradient boosting tree model, risk classification and real-time early warning are realized;Quantitative exit decision scheme is generated by combining risk level and constraint condition through multi-objective optimization algorithm.The system includes multi-source data processing, real-time feature engineering, dynamic risk early warning and exit decision auxiliary module, can realize post-investment risk whole cycle monitoring and intelligent auxiliary decision of exit scheme, improve post-investment management efficiency, reduce investment risk.

The present specification (disclosure) may relate to a method and / or a device related to link adaptation (LA) of a wireless local area network (WLAN) system. For example, the method of the present specification may relate to a method for receiving a signal including a quality of service (QoS) data frame and transmitting a signal related to LA on the basis of the received signal. For example, an STA having received the QoS data frame may transmit acknowledgement (ACK) information related to the QoS data frame and LA information related to QoS data. For example, the LA information may include modulation coding scheme (MCS) information. For example, the QoS data frame may have a preconfigured subtype field value on the basis of triggering of transmission of the LA information. For example, the ACK information may include block ACK (BA) information.

The application discloses a kind of based on perception account's vehicle-mounted memory method, system, equipment and storage medium, belongs to intelligent cabin interaction technical field.The method responds to received user voice instruction, determines and the user identity for the user identity of the unique identification user of memory function associated with the user;The semantic analysis of voice instruction is carried out and initial memory data framework containing to-be-filled field is generated;According to the workflow corresponding to the semantic type of voice instruction, a plurality of basic service interfaces for executing single basic data operation are sequentially called;Each interface return data is filled into the field corresponding to initial memory data framework, to form complete memory data;After the complete memory data is associated with user identity identification, it is uploaded to server end.The application considers user identity identification and privacy security, realizes memory function and business logic decoupling, effectively improves system scalability and interaction convenience.

The application provides a data processing method and device, electronic equipment and storage medium. The original heterogeneous IT alarm text is received, and when it is determined that the original heterogeneous IT alarm text does not have a structured rule, target privacy information of a non-IT technology dimension is located from the original heterogeneous IT alarm text, the target privacy information is replaced with a mask constant that is invariant in a global state, a desensitization intermediate state text is output, a constant template representing an IT event type and an implicit key-value pair representing a dynamic parameter value are extracted from the desensitization intermediate state text, a structured data framework is determined according to the constant template, a standard slot corresponding to the dynamic parameter type under the structured data framework is determined according to a preset semantic mapping table, a parameter value corresponding to the dynamic parameter type is filled into the standard slot, a structured data file is obtained, heterogeneous data originally in a complex discrete state is reconstructed into structure-aligned data, and a semantically consistent basic observation atlas input is provided for intelligent analysis of a back end.

Disclosed herein are systems and methods for generating notional data. The method includes: receiving seed data of one or more object types in a base dataframe; defining one or more functional relationships associated with the one or more object types, at least one functional relationship of the one or more functional relationships specifying a change to seed data of one object type of the one or more object types; generating data of the one or more object types based at least in part on the seed data in the base dataframe and the one or more functional relationships; and generating the notional data based at least in part on the generated data of the one or more object types.

The state association database construction method and device, the storage medium and the computer device provided by the application, when constructing the database, first start the time synchronization control and cumulative error correction function of the multi-source data acquisition system, and monitor the target user through the system to ensure the synchronization and accuracy of multi-source data acquisition; if a collection event that meets the event triggering rule occurs in the monitoring process, the system automatically collects multi-modal data in the preset collection window, and performs association feature mapping and cognitive label matching on the data to form a multi-element data group with a clear data framework, meeting the fine-grained modeling needs of dynamic mapping of music-induced emotions and cognitive states; after the system monitoring ends, the collected data groups are subjected to data quality verification and model adaptation verification, and after the verification is passed, they are stored in the preset multi-layer structure database in layers, and the state association database formed in this way has high reliability and usability.

The invention relates to the technical field of standard substances, in particular to a standard substance uniformity evaluation method, device and equipment based on restrictive maximum likelihood estimation, a storage medium and a computer program product. According to the method, uniformity research design is determined based on the number, batch and test conditions of standard substances; obtaining measurement data of the randomly extracted standard substance, and constructing a corresponding linear mixing effect model according to the uniformity research design and the measurement data; outlier testing is carried out on the measured data, and a data frame matched with the linear mixed effect model is generated based on a testing result; and parameter fitting is carried out on the data frame based on a restrictive maximum likelihood estimation algorithm to obtain a target evaluation result, so that the accuracy of standard substance uniformity evaluation is improved.

Methods and devices in a wireless communication network wake up from a power-save mode, receive a beacon frame, determine the received beacon frame is advertising there is buffered data traffic, staying awake for a period of time waiting for the buffered data traffic, determine there is a data frame delivering to another device in the wireless communication network, and extend the period of time waiting for the buffered data traffic in response to determining there is a data frame delivering to another device. Some embodiments extend the period of time when there is a data frame delivering to another device until the period of time reaches a maximum threshold. In some embodiments, the device determines whether the network is going to remain congested and adaptively enters the power-save mode when the network is going to remain congested.

The present disclosure relates to systems, methods, and devices for providing a centralized data store that receives and transmits data via agents that operate independently of one another. In some implementations, the agents transform data prior to transmission to the centralized data store. In some implementations, the centralized data store is configured to transform data. The centralized data store can evaluate, route, score, and otherwise manipulate and select received data. The centralized data store can respond to data requests based at least in part on its evaluation of received data.

A method for a listening network node is described herein. In accordance with one embodiment, the method includes receiving data from a serial bus interface, wherein the data includes (at least) a first header of a first data frame. The method further includes detecting completion of the reception of the first header and detecting whether the data received subsequent to the first header includes a recessive bit and storing information that indicates whether or not a recessive bit has been detected. Furthermore, the method includes detecting a stop bit in the data received subsequent to the first header and, when the detection of the stop bit fails, detecting a break delimiter that indicates the end of a break field of a second header, signaling a frame error if the stored information indicates that a recessive bit has been received, and signaling a missing response if the stored information indicates that a recessive bit has not been received.

Provided is an automatic compilation method for multiple routing operation plans in rail transit, the method comprising the following steps: step S1, identifying a selected routing type on the basis of route information of routings; step S2, constructing a unified data framework for describing input parameters of a multi-routing operation plan, and performing structured identification and data pre-processing; step S3, on the basis of transport capacity allocation objectives and requirements, establishing an operation plan optimization model which is universal to the routings and has variable input parameters, and calculating optimal time-phased plan result parameters which meet a condition; and step S4, setting up custom train numbers, matching the relationship between the custom train numbers and time-phased plans, and automatically generating a complete operation plan. Compared with the prior art, the present application has the advantages of simplifying the compilation process of operation plans, enabling easy expandability of an optimization model, meeting both a regularity condition and a customization condition, etc. Further provided are an automatic compilation system for multiple routing operation plans in rail transit, and a medium and an electronic device.

According to the state association database construction method and device, the storage medium and the computer equipment provided by the invention, when the database is constructed, the time synchronization control and accumulative error correction functions of the multi-source data acquisition system are firstly started, and low-power-consumption monitoring is performed on the target user through the system, so that the synchronism and accuracy of multi-source data acquisition are ensured; if an acquisition event meeting an event triggering rule occurs in the monitoring process, triggering a system to automatically acquire multi-modal data in a preset acquisition window, and performing associated feature mapping and cognitive tag matching on the data to form a multivariate data set with a clear data framework; the fine-grained modeling requirement of dynamic mapping of music-induced emotion and cognitive state is met; after system monitoring is finished, data quality verification and model adaptation verification are conducted on all the collected data sets, the data sets are stored in a preset multi-layer structure database in a layered mode after verification is passed, and therefore the formed state association database has high reliability and usability.

According to one embodiment, a magnetic disk drive of shingled magnetic recording (SMR), wherein user data is written to a disk with a header such as a preamble attached thereto, for each data frame including a plurality of blocks, which is a data area in a track of the disk to which the user data is written.