15 results about "Data release" patented technology

The application provides a single-machine-based large-scale graph data processing system, comprising a data loading module, a data computing module, a data releasing module, a storage management module and a disk; the data loading module is used for obtaining a subgraph with an active state from the disk and transmitting the subgraph to the data computing module; the data computing module is used for updating the subgraph and transmitting a message generated by the update to the storage management module; the data computing module is also used for transmitting the subgraph to the data releasing module; the data releasing module is used for writing the subgraph into the disk; when the subgraph is written into the disk, the storage management module is used for setting the state of the subgraph as convergent. By applying a subgraph center-based computing model to a single-machine system and establishing a unique pipeline processing architecture, the architecture can overlap data I / O and CPU operation, thereby reducing the I / O cost of a traditional vertex center computing model, improving CPU utilization, and promoting sequential access to the disk.

The application discloses a digital elevation model elevation error correction method based on a particle swarm optimization random forest, and belongs to the technical field of remote sensing. The particle swarm optimization random forest method is used for correction, so that the precision of the corrected digital elevation model is further improved. SRTM is selected as the digital elevation model used in the test, ICESat-2 strong light beam ground surface photon data is used as the reference elevation control point used in the test, Globeland30 is used as the global ground surface cover data used in the test, airborne LIDAR DTM published by NEON is used as the verification data used in the test. The method proposed in the application and the correction method based on polynomial regression are tested, the root mean square error is used as the verification index, the elevation error of SRTM can be effectively reduced, the elevation error of the corrected SRTM is reduced by 42% to 46% compared with the elevation error before correction, and the correction precision is better than that of the correction method based on polynomial regression.

The invention discloses a differential privacy-based data calling method and system in a trusted data space, and relates to the technical field of trusted authentication. The method comprises the following steps: performing classification division on target data based on sensitivity and configuring differentiated privacy budget; receiving a calling request and determining a real-time data calling level according to identity verification and trust evaluation; performing hierarchical data calling according to the level and applying corresponding differential privacy processing to generate releasable data; transmitting data through a secure channel and collecting use feedback information; and performing multi-dimensional credible verification on the requester based on the feedback information, and driving iterative calling according to a verification result and a calling request to realize dynamic lifting of a data level. According to the method, through a progressive data release and closed-loop trust evaluation mechanism, the dynamic balance between privacy protection strength and data use effectiveness is realized, the exposure risk of sensitive data is effectively reduced, and the controllability of data circulation is improved.

The application discloses a high-cost-performance all-weather antenna precise star tracking implementation method and system, and relates to the fields of antenna tracking and satellite application. The method comprises the following steps: obtaining antenna position data, satellite orbit data and bit protection data; calculating the spatial orbit position of a satellite in a future time period, generating antenna guide data after correcting the pointing error of the antenna; publishing the antenna guide data to an antenna control unit; and controlling the antenna to point to the satellite according to the antenna guide data. The antenna guide data is format data of the azimuth angle, the elevation angle and the polarization angle required by the antenna for precise star tracking at any time and any geographical position. The antenna control unit is an execution mechanism for adjusting the azimuth angle and the elevation angle of the antenna. The application simplifies the construction complexity of an antenna tracking system, shortens the construction period, and realizes the function of precise star tracking of the antenna under all-weather conditions at low cost, and is suitable for the automatic tracking of high, medium and low orbit satellites.

The invention discloses a video monitoring service method and system based on cloud computing. According to the method, the utilization efficiency of storage resources and the response performance of the system are remarkably improved through a dynamic fragmentation strategy and an intelligent popularity perception mechanism. The system can predict data access requirements in real time and adaptively adjust storage levels, high-frequency accessed real-time videos are preferentially distributed to high-speed storage nodes, and low-frequency historical data are automatically migrated to a low-cost storage area. The dynamic allocation strategy not only breaks through the physical capacity limitation of traditional local storage, but also greatly reduces the hardware maintenance and capacity expansion cost, and meanwhile, avoids single-point overload through load balancing, and ensures the service stability in a high-concurrency scene. For example, in an emergent public security event, video data in a hotspot monitoring area can be instantly switched to high-performance storage and computing resources, second-level calling and analysis are achieved, and low-activity data release resources to optimize the overall cost.

A system for conditional data release features an Orchestration Engine (OE) that enforces Immutable Governance parameters such as validation thresholds and time delays sealed in tamper-evident Vault Metadata. The OE validates governance compliance through a Cryptographic Hash Verification Engine (CHVE) confirming metadata integrity and a Time-Hash Verification Engine (THVE) recording each governance event as a cryptographically signed, time-anchored commitment. Upon successful validation, the OE initiates a hardware-isolated Secure Execution Environment (SEE) for cryptographic key operations. Payload data is sent directly to the SEE for encryption, ensuring the OE never accesses plaintext. The SEE performs encryption, key unwrapping, and decryption exclusively within its secure boundary without executing governance logic or exposing plaintext keys. Architectural separation provides a tamper-evident, time-anchored framework for conditional data release under Immutable Governance, supporting diverse conditional-execution scenarios including estate planning, database governance, and enterprise access-control workflows through modular policy frameworks.

A display device (100), comprising: a display panel (110) which is divided into a plurality of active areas (AA); a data driver (130) configured to supply data voltages to a plurality of pixels (PX) arranged in each of the plurality of active areas (AA); and a timing control device (140) configured to output a power control signal (PWRC) for controlling a driver current for the data driver (130), wherein the plurality of active areas (AA) is divided into central active areas (CA), in which a plurality of pixel columns are arranged on a central section of a plurality of pixel columns that are arranged in each of the plurality of active areas (AA), and into active periphery areas (EA), in which a plurality of pixel columns are arranged on an outer section of a plurality of pixel columns that are arranged in each of the plurality of active areas (AA), the data driver (130) contains a plurality of integrated source driver circuits (SDICs), each of which is configured to supply at least one of the data voltages to one of the plurality of active areas (AA), and the timing control device (140) is configured to generate the power control signal (PWRC) as a function of a difference value (DV) between comparison data (CD), which is a maximum data transition value between adjacent pixel rows arranged in each of the multiple active areas (AA), and edge comparison data (ECD), which is the maximum data transition value between adjacent pixel rows arranged in the multiple active edge areas (EA), wherein the time control device (140) has: a data release signal generator (141) configured to generate a sub-data release signal (SDE) configured to determine an output timing of a data voltage supplied to each of the multiple active areas (AA), and a boundary data release signal (EDE) configured to determine an output timing of a data voltage supplied to each of the multiple active boundary areas (EA); a data delay unit (142) configured to delay video data (data) by one horizontal period and output the delayed video data (D_data); a data comparison unit (143) configured to compare the video data (data) and the delayed video data (D_data) and to generate the comparison data (CD) and the edge comparison data (ECD); and a power control signal generator (144) which is configured to generate the power control signal (PWRC) using the reference data (CD) and the boundary reference data (ECD). wherein the power control signal generator (144) is configured to set a first reference value (SV1) by applying the comparison data (CD) to a first lookup table, set a second reference value (SV2) by applying the boundary comparison data (ECD) to a second lookup table, set a compensation value (CV) by applying a difference value (DV) between a first reference value (SV1) corresponding to an active area (AA) and a second reference value (SV2) corresponding to an active boundary area (EA) adjacent to the active area (AA) to a third lookup table, and add the compensation value (CV) to the first reference value (SV1) corresponding to the active area (AA) and output a result as the power control signal (PWRC).

The invention belongs to the technical field of machine vision guidance, and particularly relates to a vehicle loading machine vision guidance method. The method comprises the following steps that S1, detection equipment is arranged, specifically, a laser radar and an industrial camera are arranged in a vehicle detection area, the laser radar is used for collecting point cloud data of a vehicle and the surrounding environment, and the industrial camera is used for collecting tray related image data; s2, data acquisition: acquiring point cloud data of vehicle space coordinates and reflection intensity information through a laser radar, and acquiring depth data and color data of a tray through an industrial camera; s3, data processing: performing denoising, feature extraction, coordinate conversion and the like on the acquired point cloud data and image data; s4, core function detection; and S5, issuing the data. According to the invention, various laser radars and 2D vision technologies are fused to realize the functions of vehicle posture recognition, foreign matter detection, tray recognition, settlement monitoring and the like, and vision guidance is provided for the automatic loading and unloading vehicle.

The invention relates to an industrial network protocol test control method and device, equipment and a medium, and the method comprises the steps: calling a user-defined processing logic based on a data dynamic processing interface function, carrying out the field modification and redundant data filtering operation of an application layer load, and automatically updating an associated field containing a check code and a data length, after a processing result of the application layer load is verified through a data verification interface function, a message sending interface function sends a processed response message to target equipment, and after a test process is executed, cache data in a variable storage area is cleaned through a data release interface function; if the program instruction sequence of the current flow is executed, the network port, the cache data corresponding to the current flow in the variable storage area and the session context information are released, and the data statistics module receives network indexes including the byte number, the concurrent connection number, the network time delay and the packet loss number. According to the method, the test case development time can be greatly shortened, and the full-life-cycle maintenance cost is remarkably reduced.

The application provides a non-regular topology NoC single-multicast forwarding and deadlock avoidance method and system, and the method comprises the following steps: adopting a routing table form to perform communication data routing forwarding under a non-regular topology; adopting a regular internal fixed forwarding release method to perform deadlock avoidance and destroy a ring data flow leading to deadlock generation; constructing a NoC interconnection system according to non-regular topology information, a routing table and a release path table and configuring various routing parameters; inputting single-multicast data flow of a specific task after completion of the configuration, performing data flow forwarding and summarizing and evaluating performance. Through efficient path searching and regular data release, the application ensures that the NoC system will not be affected by potential deadlock performance caused by complex environment and increased flow under the condition of ensuring short path and low delay, solves the difficulty of routing under a non-regular topology, and has important application value and commercial potential.

A method implemented by a computer system for detecting personally identifiable information (PII) in clinical trial data before the clinical trial data is committed to a hardware storage device to improve data security, comprising: causing rendering of a graphical user interface for input of clinical trial data and one or more controls; receiving, through the graphical user interface, input clinical trial data; prior to committing the clinical trial data to a hardware storage device, associating, in memory, the clinical trial data associated with a pending state; upon determining that the clinical trial data does not include PII, accessing, from memory, the clinical trial data input into at least one of the one or more input portions; releasing the clinical trial data from the pending state; and committing the clinical trial data released to the hardware storage device.

Embedded logic analyzer (50) of an integrated circuit (10) with: a comparator block (100) configured to generate a comparator data signal (CPDT) and a plurality of comparator enable signals (CMPEN) based on an input data signal (INDT) from one of the function blocks (11-17) contained in the integrated circuit (10), such that the comparator enable signals (CMPEN) are each activated based on different comparator conditions; an operation block (200) configured to perform a logic operation on the comparison enable signals (CMPEN) to generate a data enable signal (DTEN) indicating a data acquisition time; and a packer circuit (300) configured to generate a packer data signal (PCKDT) with acquisition data and acquisition time information, based on the acquisition data signal (CPDT), the data release signal (DTEN) and a time information signal (TMINF), where the comparison block (100) contains: a plurality of comparator circuits (COMP1-COMP8), each comparator circuit (COMP1-COMP8) being configured to generate a enable signal (CMPEN1-CMPEN8) from the comparator enable signals (CMPEN) based on the input data signal (INDT) and a control signal from the comparator control signals (CMPCON) specifying the comparator control conditions, where at least one first comparator circuit of the majority of comparators (COMP1-COMP8) is configured to: Shifting of one of the input data signal (INDT) and a first shifted data signal from a second comparator circuit of the plurality of comparators (COMP1-COMP8) to generate a second shifted data signal and Comparing the second shifted data signal with a reference data signal and a third shifted data signal from a third comparator circuit of the plurality of comparators to generate the enable signal generated by the first comparator circuit.

A system for conditional data release features an Orchestration Engine (OE) that enforces Immutable Governance parameters, such as validation thresholds and time delays, which are sealed in tamper-evident Vault Metadata. The OE performs all policy validation, including invoking a Cryptographic Hash Verification Engine (CHVE) to confirm metadata integrity. Only after successful validation and satisfaction of all governance conditions does the OE route a Wrapped Data Encryption Key (DEK) to a separate, hardware-isolated Secure Execution Environment (SEE). During vault creation, payload data is sent directly to the SEE for encryption, ensuring the OE never accesses plaintext. The SEE performs key unwrapping and decryption exclusively within its secure boundary, never exposing the plaintext DEK to other components. This architectural separation of the OE's validation logic from the SEE's cryptographic execution provides a secure framework for conditional data release, preventing policy modification and ensuring plaintext keys remain isolated within a trusted hardware environment.

A system for conditional data release features an Orchestration Engine (OE) that enforces Immutable Governance parameters, such as validation thresholds and time delays, which are sealed in tamper-evident Vault Metadata. The OE performs all policy validation, including invoking a Cryptographic Hash Verification Engine (CHVE) to confirm metadata integrity. Only after successful validation and satisfaction of all governance conditions does the OE route a Wrapped Data Encryption Key (DEK) to a separate, hardware-isolated Secure Execution Environment (SEE). During vault creation, payload data is sent directly to the SEE for encryption, ensuring the OE never accesses plaintext. The SEE performs key unwrapping and decryption exclusively within its secure boundary, never exposing the plaintext DEK to other components. This architectural separation of the OE's validation logic from the SEE's cryptographic execution provides a secure framework for conditional data release, preventing policy modification and ensuring plaintext keys remain isolated within a trusted hardware environment.

1. The name of the design product: data configuration graphical user interface of electronic equipment. 2. The use of the design product: an electronic device. 3. The design points of the design product: the graphical user interface in the electronic device. 4. The picture or photo that best shows the design points: front view. 5. The electronic equipment is a conventional design, and other views are omitted. 6. The use of the graphical user interface: the product interface is an interactive interface for displaying data configuration; used for data configuration node configuration application in smart factory project; the main view interface is the interactive interface when entering the software, which is the first interface for installation and deployment, providing an integrated installation and deployment solution, including network configuration, engineer station configuration, server configuration, software installation and configuration, software data release and update, software version upgrade, etc.; in the main view interface, after clicking the left side engineering project tree - "data configuration" node, the interface change state diagram 1 is displayed, which shows the first interface of data configuration, configures the production line equipment of manufacturing enterprises in an engineering way, realizes industrial data acquisition of equipment data, and writes into real-time library and historical library. It includes data link configuration, data acquisition equipment configuration, database unit configuration, device group configuration, etc.; in the interface change state diagram 1, after clicking the left side engineering project tree - "data configuration" node under "SMT database unit", the interface change state diagram 2 is displayed; in the interface change state diagram 2, after clicking the left side engineering project tree - "data configuration" node under "production equipment", the interface change state diagram 3 is displayed; in the interface change state diagram 3, after clicking the device icon "SMT-01" in the upper middle part, the interface change state diagram 4 is displayed; in the interface change state diagram 4, after clicking the measuring point on the device (for example: "empty line pipe pressure 【A1】" in the upper right middle part), the interface change state diagram 5 is displayed.