47 results about "Data harmonization" patented technology

Embodiments of the present invention provide a system and method for data reconciliation. In one embodiment, information identifying data sources to be reconciled may be received. Data may be retrieved from a first data source based on a dynamic link identifying data in the first data source and data from a second data source may be retrieved based on a dynamic link identifying data in the second data source. A first portion of a reconciliation rule may be processed using the retrieved data from the first data source to generate a first result. A second portion of the reconciliation rule may be processed using the retrieved data from the second data source to generate a second result. The first result may be compared with the second result. If the first result matches the second result, it may be confirmed that data in the first data source is reconciled with the data in the second data source.

A data harmonization system including a data harmonization server; and one or more client devices configured to communicate with the data harmonization server. The one or more client devices may have a processor configured to transform, using a template, medical data having a first format to transformed medical data having a second format, determine whether the transformed medical data is harmonized medical data or un-harmonized medical data based on the transformed medical data and a medical imaging standard, and send the transformed medical data to a data harmonization server, if the processor determines that the medical data is un-harmonized medical data. The medical data may have a vendor specific dialect of the medical imaging standard and the harmonized medical data may have a generic version of the medical imaging standard.

Embodiments of the present invention address deficiencies of the art in respect to trusted platform module (TPM) unification in a trusted computing environment and provide a novel and non-obvious method, system and computer program product for trusted platform module data harmonization. In one embodiment of the invention, a TPM log harmonization method can include designating both a single master TPM for a master node among multiple nodes, and also a multiplicity of subsidiary TPMs for remaining ones of the nodes. The method further can include extending the single master TPM with a measurement representing a rendezvous operation for the nodes.

The invention discloses a data caching method applied to storage equipment, a control device of the storage equipment and the storage equipment. The storage equipment comprises a first cache (212) anda second cache (213). When the storage device monitors that a first data block is cached in the first cache (212) (S301), a first data block to be deleted is cached in the first cache (212) (S601), or the caching time of the first data block in the first cache (212) exceeds a threshold value (S801), obtaining feature information of the first data block, and then determining whether the first datablock is stored in the second cache (213) according to the feature information of the first data block; and if it is determined that the first data block is stored in the second cache (213) (S303, S603, S803), adjusting the level of elimination priority of the first data block in the second cache (213) (S304, S604, S804). By coordinating the data in the first cache (212) and the second cache (213) in the storage device, the response speed of the IO request is improved.

A refund tracking (RT) computing device including a processor and a memory in communication with the processor is provided. The RT computing device is configured to receive historical transaction data from a payment network or a merchant data source, the historical transaction data received in different formats, parse data fields from the historical transaction data, store the parsed data fields for each of the transactions in a respective harmonized refund data structure in a database, receive current transaction data for a current transaction from a merchant computing device, retrieve at least one harmonized refund data structure from the database, determine a refund risk score based on comparing the current transaction data to the at least one harmonized refund data structure, and transmit the refund risk score to the merchant terminal.

In an example embodiment, a demand signal management system is configured to coordinate data harmonization among a plurality of entities. The demand signal management system may obtain unharmonized data through third party entities. Global records based on internal master records and taxonomy information may be distributed to the entities. In some embodiments certain entities may have authority to create new global records. In other embodiments, some entities may have authority to approve proposed new global records. In still other embodiments, some entities may not have authority to create new global records. Unharmonzied data sent to the entities for harmonization in accordance with the global records. The entities may accept or reject the harmonization request. If accepted, the entity may return an updated global record, a proposed new global record, and / or a new global record depending on the unharmonized data, the global records and the entities' authority.

In one embodiment, a data reconciliation engine works with data store nodes included in a distributed data store system to ensure consistency between the data store nodes. In operation, the data reconciliation receives a different data snapshot from each of the data store nodes. In response, the data reconciliation engine generates one or more recommendations designed to resolve inconsistencies between the data snapshots. The data reconciliation engine then transmits each recommendation to a different data store node. Because the data reconciliation engine performs many of the resource-intensive operations included in the data reconciliation process, the resources of the data store nodes may focus primarily on processing client requests instead of performing data reconciliation operations.Consequently, unlike conventional data store node based reconciliation applications, the data reconciliation engine may process large volumes of data without unacceptably increasing the time requiredfor the distributed data store system to respond to client requests.

Methods and systems are presented for providing data consistency in a distributed data storage system using an eventual consistency model. The distributed data storage system may store data across multiple data servers. To process a request for writing a first data value for a data field, a first data server may generate, for the first data value, a first causality chain representing a data replacement history for the data field leading to the first data value. The first data server may insert the first data value without deleting pre-existing data values from the data field. To process a data read request, multiple data values corresponding to the data field may be retrieved. The first data server may then select one data value based on the causality chains associated with the multiple data values for responding to the data read request.

The present application discloses a request result determination method and device, a storage medium and an electronic device, relating to the field of data request, wherein the method includes: creating a vector data management system, wherein the vector data management system includes: data coordination node and a plurality of data working nodes, wherein each external data wrapper in the plurality of data working nodes is allowed to call the function function of the vector engine; when the data coordinating node receives a query request, control all The plurality of data working nodes call the function of the vector engine to find the request result of the query request, and the above technical solution solves the problem of low processing efficiency of the data request.

A computer-implemented method, system and computer program product are used to provide a factor in a first domain for a first set of data and in a second domain for a second set of data. The computer-implemented method, system and computer program product then determine a relationship between the domains in term of the factor. The computer-implemented method, system and computer program product determine for the first domain whether the factor from the second domain has changed, and if so, create domain specific records for the first domain in response to determining that the factor from the second domain has changed.

The present application provides a data collaborative processing method and device, which are applied to a data coordinated processing system. The data coordinated processing system includes: a mobile device and a fog node. The method includes: the mobile device obtains the data to be processed, and the The data to be processed is sent to multiple fog nodes whose coverage includes the current location of the mobile device; after receiving the data to be processed, the multiple fog nodes select a distance from the multiple fog nodes Move the device to the nearest target fog node, and establish a processing task for the data to be processed in the target fog node; if the current processing resource of the target fog node cannot handle the processing task, according to the current processing resource According to the fault type, the processing plan for the processing task is determined through the preset deep reinforcement learning network DQN algorithm; the target fog node cooperates with the cooperative fog node to process the processing according to the processing method in the processing plan Task.

The invention discloses a method for coordinating fluidized roaster data based on a novel robust estimation function, which establishes a steady-state mechanism balance model of a fluidized roaster, including a material balance equation and a heat balance equation, and constructs a novel robust estimation function. The measured value of the variable preliminarily estimates the percentage α of ZnS in the mixed zinc concentrate; this α is substituted as a known parameter into the hierarchical data coordination model in step S4 to solve the coordination value of the measured variable and the estimated value of the unmeasured variable ;Finally, the coordination value obtained from the solution is substituted into the heat balance equation to calculate the solution after coordination Problems with unknown changes.

The invention discloses a continuous variable quantum key distribution data coordination FPGA heterogeneous acceleration method, which solves the parallel acceleration problem of the SEC (slice error correction, spline error correction) protocol for data coordination in the CV-QKD system. The SEC protocol adopts multiple Level decoding method, LDPC decoding is performed at each level, and the decoding algorithm adopts logarithmic domain decoding. The parity check matrix of the LDPC code is a random sparse matrix, and decoding requires multiple BP (Belief Propagation) information iterations to correct the wrong code. The check matrix of the LDPC code used in the data coordination of the CV‑QKD system is large in scale, reaching 200,000 x 200,000, which makes storage difficult, decoding speed is very slow, and the system time is prolonged, which affects practicability. This program adopts the processing mode of CPU+FPGA heterogeneous computing based on OpenCL, parallelizes the LDPC decoding process, and proposes a static cross bidirectional circular linked list to store the check matrix of huge LDPC codes, thereby improving the The rate of the entire data coordination scheme.

The invention discloses a new type of data coordination method for continuous variable quantum key distribution. The amplitude classifiers at the sending end and the receiving end classify the screening data, and the data discrete processing unit at the receiving end performs discretization processing on the classified data and then transmits it to The sending end; the data discrete processing unit at the sending end performs discretization processing on the classified data according to the discrete data sent by the receiving end and then transmits it to the discrete data storage unit; the syndrome calculation unit at the receiving end calculates the syndrome data and sends it to the sending end ; The decoding calculation unit at the sending end performs decoding calculation to obtain the decoding result and transmits it to the receiving end; the key reorganization unit at the sending end and the receiving end performs key reorganization and integration on the decoding result data, and then passes it to the private key amplification unit to obtain Final key data. The present invention adopts a segmented error correction method to increase the code rate of error correction, thereby improving the overall security code rate and decoding efficiency of the CV-QKD system.

The invention discloses a collaborative processing method, device and system between file verification and data processing, relates to the field of data processing, and solves the security and timeliness problems of data transmission between a file verification center and a data processing center. The method includes: the file verification center processes the source data to generate an intermediate result, and stores the intermediate result in the first information list; obtains the second information list of the data coordination center; according to the comparison result between the first information list and the second information list , to update the intermediate result and the second information list of the data coordination center; the data coordination center sends a notification to the data processing center to obtain the intermediate result; The second information list: update the intermediate results and the third information list of the data processing center according to the comparison result between the third information list and the second information list of the intermediate results stored in the data processing center.