894 results about "Electronic data" patented technology

The invention provides an electronic data evidence storage verification method and system based on hierarchical hash and an intelligent contract, and relates to the technical field of block chains and data security, and the method comprises the steps: obtaining to-be-stored electronic data; to-be-stored electronic data is divided into data blocks according to a preset rule, a unique identifier and a timestamp are added to each data block, and a standardized data unit is generated; performing hierarchical hash calculation on the standardized data unit, generating a leaf node hash value by each data block, aggregating the leaf node hash values layer by layer according to a Merkle tree structure, and generating root hash; calling a block chain smart contract, submitting the tree structure hash, the timestamp and the public key encrypted signature to a block chain network, after verification of a consensus node, writing the evidence information into the block chain, analyzing a hash path submitted by a user by the smart contract to perform data verification, if the hash path is consistent with the data verification, returning verification success, otherwise, triggering an exception handling contract; through the dynamic partitioning algorithm and the layered hash structure, the calculation overhead of large file processing is reduced.

Aspects of the present disclosure provide techniques for enhanced electronic data retrieval. Embodiments include receiving a natural language query and identifying one or more electronic data sources indicated in the natural language query using a named entity recognition (NER) machine learning model trained through a supervised learning process based on training natural language strings associated with labels indicating entity names. Embodiments include determining one or more additional electronic data sources related to the one or more electronic data sources using a knowledge graph that maps relationships among electronic data sources. Embodiments include retrieving data related to the natural language query by transmitting requests to the one or more electronic data sources and the one or more additional electronic data sources and providing a response to the natural language query based on the data related to the natural language query.

A user behavior analysis system based on cloud side-end cooperation of a large language model is used for carrying out information collection, cloud side-end cooperation and user behavior analysis on mobile phones and computer equipment, and comprises an information collection module, a cloud side-end cooperation module and a user behavior analysis module. According to the invention, information acquisition is carried out on electronic data of mobile phone equipment, information privacy collaboration is carried out through the cloud side end module, and then user behavior analysis is carried out based on a large model, so that the defects of low collaboration efficiency, high user behavior identification false alarm rate and the like of an existing user behavior analysis system are overcome; the evidence obtaining efficiency and the user behavior analysis effect are effectively improved by introducing a cloud side-end cooperation and large language model, and the cloud side-end cooperation behavior analysis system which is high in efficiency, high in precision and light in weight is achieved.

Systems and methods are disclosed for preserving patient privacy while allowing health data to be analyzed, managed, and stored in different geographical areas. One method for managing cross-border health data while preserving patient privacy includes: receiving a DICOM object from a hospital computing device for analysis; generating a unique case identifier for the DICOM object; validating the received DICOM object; if, based on the validation, the received DICOM object is valid, anonymizing the received DICOM object; updating the anonymous DICOM object to include the unique case identifier; compressing the updated DICOM object; and sending the compressed DICOM object to at least one data analysis web service(s).

Systems and methods are disclosed for preserving patient privacy while allowing health data to be analyzed, managed, and stored in different geographical areas. One method for managing cross-border health data while preserving patient privacy includes: receiving a DICOM object from a hospital computing device for analysis; generating a unique case identifier for the DICOM object; validating the received DICOM object; if, based on the validation, the received DICOM object is valid, anonymizing the received DICOM object; updating the anonymous DICOM object to include the unique case identifier; compressing the updated DICOM object; and sending the compressed DICOM object to at least one data analysis web service(s).

The invention provides an electronic data security management system and method. The method comprises the following steps: acquiring an access auditing log; extracting behavior characteristics when the user accesses according to the access audit log, and further determining an intrusion risk index when the edge security node is accessed; generating an adversarial sample of the edge security node in the abnormal access mode, and determining a security policy parameter according to the adversarial sample in combination with a historical real attack sample of the edge security node; and aggregating the intrusion risk index and the security policy parameter into risk linkage information, and updating an on-chain trust certificate of each edge security node according to the risk linkage information and a historical trust value of each edge security node, thereby synchronously updating an access policy of each edge security node. By adopting the scheme of the invention, security management can be performed on the data uploaded by the edge node.

The invention discloses an electronic signature handwriting identification method based on a VILT multi-mode model. The method comprises the following steps: 1) collecting electronic signature information of a party; 2) preprocessing the collected information; 3) taking the preprocessed information as a sample; 4) constructing a multi-modal learning model based on a Transform network, namely, a VILT multi-modal model; 5) respectively sending the electronic data information and the electronic image information in the sample into a VILT multi-modal model, and carrying out model training; 6) performing optimization and parameter adjustment on the model by relying on the verification set; 7) taking the electronic signature handwriting of the party needing to be identified as a detected material, and sending the detected material into the trained and optimized VILT multi-modal model to obtain a similarity value; and 9) outputting a detection result. According to the invention, the mapping capability of the electronic image information to the electronic data information is improved, and the accuracy of electronic signature handwriting identification is improved.

A system may receive request electronic data messages and counter-request electronic data messages from various network participant nodes within a defined time interval. The system may extract data from the electronic data messages to generate input codes including indicators that characterize execution values and imputed variability levels for the electronic data messages and / or characterize the message types of the electronic data messages. The input codes are used to generate a time-interval-specific support vector machine for the defined time interval. The system may then generate dummy data including execution value and imputed variability level tuples. The dummy data is used to map boundary levels from the time-interval-specific support vector machine versus execution values.

Methods, systems, and devices include processing one or more inputs including at least one of patient-provided answers and device utilization information in association with at least one health domain, wherein the at least one health domain is associated with one or more chronic conditions, determining one or more states of a patient in association with the at least one health domain based at least in part on processing the one or more inputs, and storing information describing the one or more states in an electronic data record.

Disclosed is a storage cabinet. An embodiment has one or more shelves, one or more doors for enclosing the cabinet, and an electromagnetic lock for locking the door or doors. The shelves have one or more cameras, an opened- or closed-door state sensor, and a weight sensor arranged to measure weight of products placed on said shelves. An electronic data processor carries out a machine learning computer vision method for processing data received from cameras and sensors to identify products removed from said shelves. The processor detects when a cabinet door is in an open state, acquires image and weight data from the associated camera and weight sensor. When a weight change at a shelf is detected, processing of image data acquired including when the weight change occurred occurs, with said machine learning computer vision method.

A system is provided for intelligent automated simulation of penetration testing and isolation of vulnerable distributed electronic data registers. In particular, the system may extract metadata regarding one or more nodes or sections of a distributed register. Based on the metadata, the system may generate a knowledge graph that may indicate the vulnerabilities associated with particular nodes, blocks, and / or sections of the distributed register. Based on the knowledge graph, the system may compute vulnerability scores for the various nodes, blocks, and / or sections, and generate a vulnerability heatmap based on the scores. The system may further be configured to allow a user to perform automatic simulated penetration tests on the vulnerable portions of the distributed register and / or execute one or more remediation process on such vulnerable portions. In this way, the system provides an efficient way to identify and remediate vulnerabilities within a distributed register.

The invention belongs to the technical field of archive management, and discloses an intelligent archive supervision method, device and equipment and a storage medium, and the method comprises the steps: carrying out the standardization processing of an archive feature data set which is established based on entity feature information and electronic feature information, and generating the digitalized archive information which can be analyzed; processing the parsable digital archive information through a preset rule to obtain archive metadata; constructing a dynamic supervision model based on the file metadata, and performing real-time association analysis by using the dynamic supervision model; when the correlation analysis result does not meet the preset condition, a corresponding grading response mechanism is matched according to the label attribute, and a disposal instruction containing an exception type identifier is generated; and outputting a visual supervision report based on the execution result of the disposal instruction and the historical supervision data, thereby breaking through the limitation of physical feature and electronic data splitting analysis, establishing entity-electronic feature space-time correlation mapping, and realizing accurate matching of hierarchical response strategies based on file metadata tags.

Computer implemented systems and methods are disclosed for importing data from electronic data files. In accordance with some embodiments, a file format is assigned to a source electronic data files by a data importation system. The data importation system may further identify a file type identifier associated with the source electronic data file and map the source electronic data file to a transformation template. The data importation system may further store the file format, file type identifier, and an indication of the transformation template as a file type profile associated with the source electronic data file in a database.

The invention discloses a hierarchical acquisition and analysis method and system for attribute information of a cultural relic building, and belongs to the field of electronic data analysis. According to the method, the acquired historical stored data of the cultural relic building is imported into a danger assessment strategy for cultural relic building danger assessment, maintenance judgment is performed, quantitative assessment is performed based on the damage condition of the cultural relic building, and whether the building needs to be maintained is judged according to a quantitative assessment result, so that the safety of the cultural relic building is improved; meanwhile, structure maintenance analysis is carried out according to structure composition importance and structure composition dangerousness before maintenance, and then accurate judgment of maintenance steps is carried out.

The invention relates to the technical field of engineering management, and particularly discloses a building engineering management system and a management method thereof, and the method comprises the steps: carrying out the semantic analysis of electronic data of a target labor service worker through employing a data processing technology based on deep learning, so as to extract the identity information feature of the labor service worker, and meanwhile, in combination with pre-formulated construction requirement rules, semantic query response coding is performed on the identity information of the labor service personnel and a large number of construction requirement rules, so that a potential matching relationship between the labor service personnel and the construction project is mined, and intelligent assessment of the adaptability of the labor service personnel is realized. According to the method, whether the labor service personnel meet the specific requirements of the construction project or not can be evaluated more comprehensively and accurately, and the construction problem caused by insufficient skills or lack of experience of the labor service personnel is effectively avoided.

A system is provided for detection and mitigation of unauthorized reproduction of sensitive electronic data. In particular, the system may comprise a networked environment with various computing devices that may be used to store, process, and / or transfer sensitive electronic data. When a user accesses the sensitive data, the contents of the data may be presented as a series of micro dots or pixels. The system may be configured to display rapidly change at least a portion of the micro dots or pixels at a high frequency, such that a snapshot of the sensitive data taken at a singular point in time will not be able to capture all of the data needed to make the data readable to the user. In this way, the system may be able to prevent the unauthorized reproduction of sensitive data within the network environment.

To support various tasks related to the employment of foreign nationals, such as through electronic applications. [Solution] The electronic application support device 1 related to the employment of foreigners of the present invention comprises a foreigner data management unit 111 that manages foreigner data including information regarding the employment of foreigners, a definition file management unit 112 that manages definition files for generating, based on the foreigner data, electronic application data to be sent when submitting an electronic application for the employment to the Immigration Bureau, an electronic application data generation unit 114 that generates electronic application data based on the foreigner data and the definition file, and a verification unit 116 that verifies the validity of the electronic application data, and the verification unit 116 is configured to at least verify whether the foreigner's work visa is within the expiration date and not provide a verification result that the electronic application data is valid if it is not within the expiration date.

The present disclosure includes a system for generating and distributing data records representing quotes for legal services. The data records are generated at a server in response to a request from a client device. The data records are based on parameters received from a plurality of platforms, the parameters representing estimated costs for providing services. The server determines a subset of data records to transmit to the client device based on the parameters, the request, and a rating.

The invention discloses a geological archive electronic data security storage method and system based on a block chain, and relates to the technical field of geological information data security, and the method comprises the steps: constructing a multi-modal Merkle sub-tree based on a cross-modal alignment key set, aggregating the multi-modal Merkle sub-tree into a cross-modal Merkle forest root, calculating a cross-modal consistency index, and generating an inconsistent item list; according to the multi-modal consistency index and the inconsistent item list, obtaining a differential security domain mapping table and an access condition set of the geological archive data, and respectively generating a verifiable desensitization proof of a restricted domain and a verifiable zero-knowledge proof of a confidential domain; and packaging the cross-modal Merkle forest root, the differentiated security domain mapping table, the access condition set, the verifiable desensitization proof and the verifiable zero-knowledge proof into an uplink abstract package, verifying the desensitization proof and the zero-knowledge proof through an intelligent contract, and generating a transaction record hash and a new block candidate. According to the invention, the security of the electronic data of the geological archive is improved.

To verify compliance with a data access policy, the system compares electronic data to an electronic data access policy identified by a database; determines whether a portion of the electronic data complies with the electronic data access policy; in response to the portion of the electronic data not complying with the electronic data access policy, indicates that an access to the electronic data by a communication device is not permissible; and declines the access to the portion of the electronic data to the communication device when the access to the electronic data is not permissible. Related methods and computer program products are also discussed.

Aspects of the present disclosure relate to automated evaluation of electronic datasets. Embodiments include receiving one or more rules related to evaluation of electronic datasets. Embodiments further include generating, via an embedding model, embedding representations of the one or more rules. Embodiments further include receiving an electronic dataset. Embodiments further include identifying a rule that is applicable to the electronic dataset based on using a machine learning model configured to search the embedding representations of the one or more rules based on the electronic dataset. Embodiments further include evaluating, using the machine learning model or an additional machine learning model, the electronic dataset based on the identified rule. Embodiments further include using the machine learning model or the additional machine learning model to generate an evaluation summary for the electronic dataset based on determining that an item within the electronic dataset does not comply with the identified rule.

A computer system is disclosed that provides purpose-based control of user actions and access to electronic data assets. For example, the computer system may perform operations including: receiving, from a user, a request to perform an action; determining any checkpoint config objects associated with the action; displaying checkpoint dialog based on checkpoint config object; determining whether criteria associated with the checkpoint object are satisfied; and in response to determining that the criteria associated with the checkpoint object are satisfied: generating a checkpoint record object; and proceeding to perform the action.

In accordance with at least one aspect of this disclosure, there is provided, an artificial intelligence / machine learning (AI / ML) data aggregation module configured to aggregate and parse electronic data from a plurality of systems (e.g., which system(s) may be based on a site location / building) each including a plurality of assets / devices, for determining one or more analytics (e.g., trends) for the assets / devices. In certain embodiments, the AI / ML aggregation module can be configured to receive system data directly and in real time from each of the plurality of systems through one or more communication channels and media formats.

Obtaining first electronic data of a first user. Obtaining second electronic data for each of a plurality of second users, obtaining first electronic data of a first user. Obtaining second electronic data for each of a plurality of second users. Determining first input data for at least one first machine learning model based on the first electronic data of the first user. Predicting, based on the first input data and the at least one first machine learning model, a first mental state of the first user, the first mental state comprising a set of first mood values, a set of first uncertainty values, and a set of first magnitude values, each first mood value of the set of first mood values being associated with a corresponding first uncertainty value of the set of first uncertainty values and a corresponding first magnitude value of the set of first magnitude values, the first magnitude value indicating a first relative strength or weakness of the associated first mood value. Predicting, based on the first mental state of the first user, the second electronic data for each of the plurality of second users, and one or more second machine learning models, one or more therapeutic matches between the first user and one or more second users of the plurality of second users. Facilitating presentation, via a graphical user interface (GUI), of the one or more therapeutic matches. Receiving, in response to the first user interacting with the GUI, a user selection of a particular second user of the one or more second users of the plurality of second users. Automatically connecting, in response to receiving the user selection of the particular second user of the one or more second users of the plurality of second users, the first user with each of the one or more second users of the plurality of second users.

The invention relates to the technical field of electronic data digital processing, and discloses a data maintenance management method and system based on artificial intelligence. The method comprises the following steps: acquiring multi-dimensional features such as an access time sequence, metadata, an association relationship and a service context of data; constructing a hybrid model fusing a long-short-term memory network and a graph attention network, and predicting a future value score of the data; dynamically generating a hierarchical storage, archiving or deleting strategy based on the score and storage cost-performance model; and through the access feedback after the execution of the monitoring strategy, the prediction model is optimized in a closed-loop manner by using a reinforcement learning mechanism. The system comprises a data feature acquisition module, a value prediction module, a strategy generation module and an execution feedback module. According to the method, self-adaptive, refined and intelligent management of the full life cycle of the data is realized, the utilization efficiency of storage resources is remarkably improved, and the operation and maintenance cost is reduced.

Various embodiments relate generally to data science and data analysis, computer software and systems, and control systems to provide a platform to implement automated responses to data representing electronic messages, among other things, and, more specifically, to an automated predictive response computing system independent of electronic communication channel of an electronic message payload, the automated predictive response computing system being configured to, for example, implement a universal data space based on, at least in part, conversational data flows, which may be classified and used to provide a predictive response to assist resolution, such as assisting an agent among other things. In an example, a method may include augmenting at least a subset of one or more portions of communication data, implementing augmented communication portion data to determine a predicted response, and generating data to facilitate the predicted response based on the subset of inbound electronic messages.

Systems and methods provide efficient access to electronic data capture (EDC) and electronic medical record (EMR) data for monitoring clinical research. A multi-tenant clinical research platform is configured to support remote management of clinical research sites based on EDC and EMR data. The platform is configured to access EDC data from an EDC data store, access related EMR data from an EMR data store that is separate from the EDC data store, and use mappings between the EDC data and the EMR data to contextually integrate the EMR data into a clinical research review workflow provided by the platform. In some embodiments, the platform is configured to prevent persistence of the EDC data and / or EMR data within the platform. The platform provides remote, on-demand controlled access to the EDC data and the EMR data to facilitate offsite reviews of clinical research sites based on EDC and EMR data.

The invention discloses an aircraft general assembly information association rule mining method and device based on a fine tuning large language model and a medium, and relates to the field of electronic data digital processing, the method comprises the following steps: S1, collecting multi-source production element data in an aircraft general assembly process file; s2, performing field adaptation by a large language model fine tuning method based on low-rank adaptation; s3, extracting structured element information, and constructing a semantically optimized item set; s4, mining association rules of the production elements and the final assembly links based on an association rule mining algorithm; and S5, optimizing and outputting a high-confidence association rule set. According to the method, the accuracy of information extraction and the depth of production element association analysis are effectively improved by combining fine adjustment of a large language model with association rule mining, introduction of a low-rank matrix and deep combination of a mining algorithm, so that the recognition precision of the association relationship between production elements is greatly improved; and reliable data support and decision basis are provided for optimization of the final assembly process.

Systems, computer program products, and methods are described herein for validation of electronic data transfers in a distributed network via self-directed image data. The present invention is configured to receive a request for a transfer of electronic data from a first repository associated with a first user to a second repository associated with a second user, transfer the electronic data, generate and apply a first identifier to the electronic data, collect a geolocation of a second endpoint device, transmit the geolocation and a request for a verification of the geolocation to the first endpoint device, receive the verification of the geolocation, generate and apply a second identifier to the electronic data, transmit control signals to the second endpoint device to prompt collection of self-directed image data, and collect, using the second endpoint device, the self-directed image data.

The invention discloses an intelligent question and answer generation method and system based on a large language model, and relates to the technical field of data information analysis, and the method comprises the following steps: obtaining electronic data, and storing the electronic data in a relational database; the method comprises the following steps: carrying out training on an Embedding Model; generating corresponding first vector data from the training data, and storing the first vector data, the first SQL statement and the answer content into a vector database; obtaining a user question, vectorizing the user question through an Embedding Model to obtain second vector data, and generating a cue word through vector recall; and inputting the cue word into the first large language model to obtain a second SQL statement, and executing the second SQL statement in the relational database to obtain a query result. According to the method and the device, the complexity of table design is reduced in the data storage stage, and the processed structured data is stored in the relational databases with different themes. And interacting with corresponding relational databases aiming at different topics, and quickly querying, positioning and analyzing data.