56 results about "Derived Data" patented technology

The invention discloses a data security management method and system based on AI drive, and relates to the technical field of artificial intelligence and data security, and the method comprises the steps: generating a fusion feature vector through a multi-modal feature extraction and semantic alignment mechanism; constructing a blood relationship knowledge graph, performing graph embedding calculation on the blood relationship knowledge graph to obtain a graph embedding vector, and calculating a blood relationship propagation sensitivity score; generating a sensitivity evaluation result through a dynamic decision neural network in combination with context features of the data access request; generating and executing an access control strategy according to a sensitivity evaluation result, and triggering cascade label evaluation on downstream derivative data along a blood relationship knowledge graph; and selecting samples based on confidence, submitting the samples to manual auditing, and executing incremental learning updating on model parameters according to auditing feedback. According to the method, the sensitivity identification accuracy of cross-modal data is improved through multi-modal semantic fusion, and automatic cascade updating of sensitive tags is realized through a blood relationship propagation mechanism.

This invention relates to the field of communication data processing, specifically to a method and system for ship identification in multi-channel communication. It includes: acquiring historical multi-channel communication data; determining batch camouflage verification data based on camouflage verification data; acquiring a batch ensemble classifier and a local ensemble classifier; determining first derived data and second derived data based on the batch camouflage verification data and normal verification data; determining the batch camouflage verification data with updated weights based on the first and second derived data; determining an overall ensemble classifier; acquiring target multi-channel communication data; determining target batch data from the batch camouflage verification data with updated weights based on the target feature vector; and determining the detection result corresponding to the target multi-channel communication data based on the target batch data and the overall ensemble classifier. This invention can improve the accuracy of ship identification.

Disclosed are methods comprising determining experimental data associated with one or more monoclonal antibodies (mAbs), determining computationally-derived data associated with the one or more mAbs, wherein the computationally-derived data comprises one or more computational parameters weighted based on accessible surfaces (ASAs) of one or more residues of the one or more mAbs, determining, based on the experimental data and the computationally-derived data, a plurality of candidate predictive models, determining an optimal predictive model from the plurality of candidate predictive models, and outputting the optimal predictive model. 20 26 20 53 60 07 J ul 2 02 6 A B S T R A C T D i s c l o s e d a r e m e t h o d s c o m p r i s i n g d e t e r m i n i n g e x p e r i m e n t a l d a t a a s s o c i a t e d w i t h o n e o r 2 0 2 6 2 0 5 3 6 0 0 7 J u l 2 0 2 6 m o r e m o n o c l o n a l a n t i b o d i e s ( m A b s ) , d e t e r m i n i n g c o m p u t a t i o n a l l y - d e r i v e d d a t a a s s o c i a t e d w i t h t h e o n e o r m o r e m A b s , w h e r e i n t h e c o m p u t a t i o n a l l y - d e r i v e d d a t a c o m p r i s e s o n e o r m o r e c o m p u t a t i o n a l p a r a m e t e r s w e i g h t e d b a s e d o n a c c e s s i b l e s u r f a c e s ( A S A s ) o f o n e o r m o r e r e s i d u e s o f t h e o n e o r m o r e m A b s , d e t e r m i n i n g , b a s e d o n t h e e x p e r i m e n t a l d a t a a n d t h e c o m p u t a t i o n a l l y - d e r i v e d d a t a , a p l u r a l i t y o f c a n d i d a t e p r e d i c t i v e m o d e l s , d e t e r m i n i n g a n o p t i m a l p r e d i c t i v e m o d e l f r o m t h e p l u r a l i t y o f c a n d i d a t e p r e d i c t i v e m o d e l s , a n d o u t p u t t i n g t h e o p t i m a l p r e d i c t i v e m o d e l .

This invention discloses a method for processing multimodal data acquisition in intelligent manufacturing systems, relating to the field of industrial data governance technology. The method includes: acquiring multimodal data streams; segmenting raw data blocks and standardizing and encapsulating them to generate metadata records; establishing time indexes, batch indexes, and process indexes; hashing the metadata records to generate content addresses and writing them to object storage; recalculating the hash and comparing the content addresses to complete consistency verification and writing the results to a commit log table; generating operator records for successfully committed data blocks and hashing them to obtain operator addresses; registering lineage edges to form directed acyclic lineage relationships; generating leaf lists according to a preset range and aggregating them to obtain root digests; verifying content addresses object by object based on the leaf lists and root digests; replaying and recalculating to generate replay-derived data blocks; comparing them to generate audit records and storing them. This invention ensures continuous monitoring of data quality during big data acquisition through the replay and recalculation processing of directed acyclic lineage relationships.

This application discloses a method, system, device, and computer medium for generating 3D models of urban rail transit, relating to the field of digital twin modeling and 3D visualization technology for urban rail transit. The method involves acquiring diverse and heterogeneous data of urban rail lines, including 2D design drawings and derived data; processing the diverse and heterogeneous data to generate a basic dataset for the urban rail lines; acquiring user-defined configuration data for the urban rail lines; integrating the basic dataset and the user-defined configuration data to obtain a target dataset for the urban rail lines; identifying 3D model elements matching the target dataset for the urban rail lines from a pre-set model library; and rendering the 3D model elements according to the target dataset to generate a 3D model of the urban rail lines. This method ensures that the generated 3D urban rail models meet user needs, provides diversity and flexibility in model construction, improves model scalability, reduces the degree of human intervention, and enhances the efficiency of urban rail modeling.

The invention provides a radio pulsar searching method, system and equipment, and the method comprises the steps: obtaining observation data of a radio telescope, and carrying out the processing of the observation data, so as to generate a plurality of groups of time series data corresponding to a plurality of dispersion quantity channels; performing staged periodic signal search on each group of time sequence data, and processing each group of time sequence data or derived data formed by each group of time sequence data according to a generated quasi-period to generate feature data of a plurality of candidate bodies; inputting the feature data of the plurality of candidate bodies into a pre-trained classification model to obtain a classification result representing the credibility of the plurality of candidate bodies as a target signal; and obtaining a comprehensive score of the plurality of candidate bodies, and sorting the plurality of candidate bodies according to the comprehensive score to generate a pulsar candidate body list.

The registration machine is configured to derive a data key by using a plaintext word representing a word which is not encrypted, create encrypted data obtained by encrypting, by using the derived data key, plaintext data representing data which is not encrypted, distribute the data key to a plurality of shares, and encrypt the plaintext word and the shares with searchable encryption to create an encrypted word. The analyzer is configured to encrypt, with the searchable encryption, a plaintext query representing a query which is not encrypted to create an encrypted query. The provision server is configured to acquire the created encrypted word and the created encrypted data to register the encrypted word and the created encrypted data in a database, acquire the created encrypted query to compare the created encrypted query with the registered encrypted word, and acquire the shares if a comparison result indicates a match.

The invention discloses a data desensitization method and device, a storage medium, electronic equipment and a program product, and relates to the field of financial science and technology and the field of information security, and the method comprises the steps: constructing a blood relationship dependence graph based on a data processing link; determining the blood relationship dependence intensity of the derivative data on the original sensitive data according to the blood relationship dependence map, wherein the blood relationship dependence intensity represents the probability of obtaining the original sensitive data after leakage of the derivative data; determining the desensitization intensity of the target business data according to the sensitive field in the target business data, the scene identifier and the sensitivity level of the target business data and the blood relationship dependence intensity, and then determining a desensitization strategy according to the desensitization intensity; and performing desensitization processing on the target business data according to the desensitization strategy, and outputting the desensitized target business data. According to the method and the device, the technical problem of high desensitization leakage risk caused by incapability of effectively tracking and identifying derivative sensitive data in a desensitization technology in the prior art is solved.

This invention discloses an AI-based data management system and method for production machinery operation, belonging to the field of industrial data management technology. The method includes: real-time acquisition of raw time-series data and derived data during the operation of production machinery, and extraction of data feature information; construction of a data value assessment model to score the total value of the data and predict access popularity, generating storage tags; construction of a data hierarchical decision model based on the storage tags, comprehensively analyzing real-time data access patterns, storage costs, and lifecycle stages, generating dynamic hierarchical instructions to dynamically allocate data to corresponding storage levels; real-time monitoring of data access patterns, dynamically adjusting storage tags, and triggering data migration operations to optimize storage performance and access efficiency. This invention improves the access speed of critical data and reduces the storage cost of low-value data through AI-driven dynamic data hierarchical storage.

A method for restoring missing sampling points in an array spectrometer leverages the advantages of Fourier interpolation. By adding high-frequency zero values ​​in the frequency domain, it reduces the sampling interval of spectra without missing points, thus increasing the amount of sampled data. In principle, if the original data has sufficient sampling density, Fourier interpolation offers higher accuracy compared to local interpolation. This invention proposes utilizing the distribution characteristics of spectral peaks to reset the sampling density of the original data. After meeting the interpolation prerequisites, it extracts higher-density Fourier interpolations to compensate for the sampling deficiencies in the original data, obtaining estimates with higher accuracy than linear interpolation and spline interpolation. The benefits of this invention are twofold: firstly, it obtains higher-accuracy completed values; secondly, because it does not alter the frequency distribution characteristics of the spectrum, it ensures the processing accuracy of the derived data.

Embodiments of the present application provide a data usage updating method, device and system, which can improve the accuracy of data usage statistical results. The method comprises: a user plane function entity receiving a derived data packet of a first downlink data packet from an access network device, wherein the derived data packet is obtained according to the first downlink data packet, and the derived data packet comprises a first identifier; the user plane function entity determining, according to the first identifier, that the first downlink data packet is a discarded data packet; and the user plane function entity sending data usage updating information to a session management entity, wherein the data usage updating information is used to deduct the data usage of the first downlink data packet.

A data transformation system for implementing reproducible and consistent data transformations in multiple execution contexts (batch, streaming, etc.) where the transformation function / logic initially acts on historical raw data to produce derived data to train a machine learning model. When the model is trained and deployed to handle streaming event data, the same transformation is reused to transform streaming data into the appropriate derived data for the model scoring, and later for a refit of the model.

To provide a system and a method for executing information processing related to data representing information while keeping the information secret by encryption.SOLUTION: In a secret information processing system including a registration machine, an analyzer, and a providing server connected via a network, the registration machine derives a data key by using a plaintext word, creates encrypted data obtained by encrypting plaintext data by using the derived data key, distributes the data key to a plurality of shares, and creates an encrypted word by encrypting the plaintext word and the shares by searchable encryption. The analyzer encrypts a plaintext query with searchable encryption to create an encrypted query, and the provision server acquires an encrypted word and encrypted data, registers the encrypted word and the encrypted data in a database, acquires the encrypted query, compares the encrypted query with the registered encrypted word, acquires a share when a comparison result is a match, restores a data key when the acquired share is a certain number or more, and decrypts the encrypted data into plaintext data using the restored data key.SELECTED DRAWING: Figure 7

To provide a data evaluation system, data evaluation method, and program that can evaluate data that does not have an explicit relationship with other data. [Solution] The data evaluation system according to this disclosure comprises a management unit that manages the history information of one or more data to be evaluated; an extraction unit that extracts related information of the history data, including at least one of the source data or derived data of the data to be evaluated, based on the history information; and an evaluation unit that evaluates the data to be evaluated based on the extracted related information.

Artificial intelligence (AI) oversight may be added to a multiparty engagement, such as a conference between devices having user interfaces. The AI may apply visual indicators, e.g., informational elements, recommendations, or other data, on one or more user interface. Visual indicators assist with presenting or participating in a conference. Visual indicators may highlight, e.g., AI-determined attributes of participants in the conference. Attributes may be derived physiological characteristics of participants, such as mood, apparent interest, paying attention, as well as AI-derived data from analyzing data sources, such as data about the participant, past engagements, time zone, name / title and other information to facilitate interaction with the participant. The AI may also review data for past deals, resume, project plans, social media, customer relationship manager data, and the like and develop models to allow it to monitor a conference and provide recommendations to facilitate conference goals.

This application provides an automatic mapping method and system for lunar impact crater micromorphology, belonging to the field of image data processing technology. The method involves acquiring a candidate raster dataset, including lunar digital terrain data, lunar image data, and terrain-derived data; the terrain-derived data includes multiple terrain-derived factors; filtering the candidate raster dataset to determine the optimal feature combination; combining the optimal feature combination with the labels of impact crater micromorphology subclasses to construct an impact crater micromorphology subclass dataset; inputting the impact crater micromorphology subclass dataset into a pre-built deep learning model for training to obtain a target model; and using the target model to automatically extract impact crater micromorphology subclasses across the entire lunar surface, thereby completing the mapping of the entire lunar landscape. This solution alleviates the current problem of insufficient efficiency in extracting impact crater micromorphology subclasses primarily through manual extraction, providing the possibility for high-precision and rapid mapping of the entire lunar landscape.

In order to provide a method for detecting changes in behaviour and / or changes in properties of technical systems, by means of which in particular physical changes in behaviour or changes in properties of parts or components of the technical system can be detected, a method (100) for detecting changes in behaviour and / or changes in properties of technical systems (10) is proposed, wherein: state data relating to at least one component (12) of a technical system (10) are received and / or queried by a data processing device (17) of the technical system (10) via a communication bus (16); the state data and / or data derived from the state data by the data processing device (17) are transmitted via a communication network (22) to an external computing device (19); the external computing device (19) determines, from the state data and / or the derived data, whether a change in state of the at least one component (12) over time has occurred, and compares the change in state over time with a predetermined criterion; and the computing device (19) determines a change in behaviour and / or change in properties of the technical system (10) if the change in state over time satisfies the predetermined criterion.

Systems, methods, and computer-readable media are provided for generating natural language project summaries via large language models including deterministically derived data value narratives. A computer-implemented method includes processing a first input configuring data stored in association with a plurality of fields, generating a narrative for a project, and causing display of the narrative in a report for the project. The narrative is generated by applying one or more deterministic operations to derive one or more values for the project based at least in part on at least one field of the plurality of fields, based at least in part on the configured data, generating a prompt, prompting a large language model with the prompt to generate a result, and storing the result as the narrative for the project. The prompt includes the one or more derived values and a context comprising the project for which a narrative is being generated.

A system that performs calculations on encrypted data has a registry machine, an analyzer, and a delivery server connected via a network. The registry machine derives a data key from a plaintext word, generates encrypted data obtained by encrypting plaintext data using the derived data key, distributes the data key to a multitude of shares, and encrypts the plaintext word and shares using a searchable cipher. The analyzer then uses this searchable cipher to encrypt a plaintext query.The deployment server is configured to capture the encrypted word and the encrypted data and register them in a database, to capture the encrypted query to compare it with the encrypted word, and to capture the shares. If a comparison result shows a match, and if the number of captured shares is a certain number or more, to reconstruct the data key that has a correspondence relationship with the multitude of shares, and to use the reconstructed data key to decrypt the encrypted data into the plaintext data.

Provided are systems and methods for providing insights to users of a mobile application based on triggers that may be detected from within the data or externally. In one example, a method may include receiving, via a message transmitted to a uniform resource locator (URL) of a host platform, information about a user of a software application, reading a plurality of records associated with the user from the received information, the plurality of records comprising data and a plurality of timestamps, respectively, generating derived data based on the data included in the plurality of records, converting the plurality of timestamps into a single timing identifier that represents all of the plurality of timestamps, and transmitting, to a computing system, a notification comprising the derived data and the new timing identifier.

The application provides a multi-dimensional health data processing system and method for internal medicine patients, which performs dimensional filtering on multi-dimensional health data flow through priority scores of each independent data dimension to obtain first intermediate data; performs correlation degree learning on orthogonal coupling relationships between each independent data dimension based on the first intermediate data to obtain a time-varying nonlinear strength coupling matrix, and then performs sparse reconstruction on the correlation topological structure between each independent data dimension according to the strength coupling matrix to obtain second intermediate data; and finally, based on the second intermediate data, a derived data view of the current application scenario is obtained in response to an external query condition of the current application scenario, and the common feature mode of the internal medicine patient group is visually presented using the derived data view. Based on the above scheme, dimensional correlation reconstruction of multi-dimensional health data can be realized, thereby improving the scene adaptability of internal medicine health data processing.

Systems and methods for dynamically selecting source code development tests using a trained machine learning (ML) model are disclosed. In certain embodiments, a plurality of data features is derived from information indicating a plurality of modifications to a source code repository. Based at least in part on the derived data features, an ML model is trained to identify correlations between the modifications and a plurality of historical source code development test results. Upon receiving an indication of one or more additional modifications to the source code repository, the trained ML model dynamically selects, from a plurality of source code development tests, a subset of source code development tests relevant to the additional modifications.

Systems, methods, and computer-readable media are provided for generating natural language project summaries via large language models including deterministically derived data value narratives. A computer-implemented method includes processing a first input configuring data stored in association with a plurality of fields, generating a narrative for a project, and causing display of the narrative in a report for the project. The narrative is generated by applying one or more deterministic operations to derive one or more values for the project based at least in part on at least one field of the plurality of fields, based at least in part on the configured data, generating a prompt, prompting a large language model with the prompt to generate a result, and storing the result as the narrative for the project. The prompt includes the one or more derived values and a context comprising the project for which a narrative is being generated.

The invention relates to the technical field of payment settlement, and discloses a scientific and technological achievement transaction fund automatic settlement method and system based on a smart contract, and the method comprises the steps: compiling a transaction parameter based on a transaction intention, obtaining a contract byte code, deploying the contract byte code to a block chain, and obtaining a unique contract address. The buyer locks transaction funds to the contract account, and meanwhile, an achievement delivery file uploaded by the seller is encrypted and fragmented to generate derived data segments; the derived data segments are distributed to distributed storage nodes, and storage addresses and content hash values returned by the nodes are combined into a fragment index list according to an agreed format; and extracting digital voucher information of the delivery file from the list, and performing byte verification on the digital voucher information and a seller digital voucher sample in the transaction parameters to obtain a content acceptance result. And finally, according to a settlement identifier in an acceptance result, automatically determining a transfer direction of funds of the two transaction parties. According to the invention, the efficiency of scientific and technological achievement transaction fund automatic settlement based on the smart contract can be improved.

An apparatus and method for federated fraud risk management. Signals from multiple entities engaged in financial, transactional, or compliance data exchange are securely ingested, normalized, and enriched with external and internal data. A scoring module employs one or more analytical techniques, such as statistical methods or neural and non neural models, to compute one or more risk scores across multiple operational, transactional, or identity linked dimensions. A decision component generates and transmits alerts to authorized systems and may route, hold, or escalate operations based at least in part on the computed score. The apparatus and method support privacy preserving collaborative training using techniques such as federated learning, homomorphic encryption, or approaches. Processing may escalate to external systems, generate or update a record, or supply derived data for model retraining. The operations may be performed in any order or in parallel.

The invention provides an off-line and on-line integrated feature derivation method and a related device. The off-line and on-line integrated feature derivation method is applied to a feature derivation system. The method comprises the following steps: determining a target derivation mode, wherein the target derivation mode comprises an offline mode and an online mode; determining a feature package and a derivation task according to the target derivation mode; the feature packet comprises one or more of original data, derivative data and custom data; performing derivation calculation on the feature packet according to the derivation task to generate a feature wide table; the feature wide table comprises a plurality of derivative features and is used for model training or data analysis; wherein the derivative calculation modes of the offline mode and the online mode are the same. Therefore, the same set of calculation scheme can be used for both off-line derivation and on-line derivation, so that off-line and on-line data can be directly converted, and the off-line and on-line data conversion efficiency is improved.

The invention provides a task data acquisition method and device, electronic equipment and a medium. According to the specific implementation scheme, the task data acquisition method comprises the steps that at least one view and at least one basic operator associated with a service scene task are acquired; in response to an arrangement operation for the at least one view and the at least one basic operator, determining a first arrangement structure comprising the at least one view and the at least one basic operator; in response to a configuration operation for the target basic operator, determining configuration information of the target basic operator, the configuration information comprises a first target operation executed on a first target field of the target view by using a target basic operator, a newly added derivative field of a derivative view output by the target basic operator relative to the target view, and a second target operation required to be executed for obtaining derivative data represented by the derivative field; according to the first arrangement structure and the configuration information of each target basic operator, a result view is generated, and the result view is used for obtaining task data associated with the business scene task.

The present specification provides a radio pulsar searching method, system and device, comprising: obtaining observation data of a radio telescope, and processing the observation data to generate a plurality of sets of time series data respectively corresponding to a plurality of dispersion measure channels; performing a phased periodic signal search on each set of time series data respectively, processing each set of time series data or derived data composed of each set of time series data according to the generated quasi-period to generate feature data of a plurality of candidates; inputting the feature data of the plurality of candidates into a pre-trained classification model to obtain a classification result representing the credibility of the plurality of candidates as target signals; obtaining a comprehensive score of the plurality of candidates, and sorting the plurality of candidates according to the comprehensive score to generate a pulsar candidate list.

Methods, systems, and computer program products are described herein that provide a serverless, multi-engine, multi-user data lake indexing subsystem and application programming interface. Indexes are defined as derived datasets and stored in a common format on a data lake, enabling different engines to create and / or discover indexes for workload optimization. Embodiments of indexes enable state control and management of indexes via metadata included in the indexes and stored on the data lake.

The invention discloses an anomaly detection method and device for a base station, equipment and a storage medium, and the method comprises the steps: obtaining a configuration data set of the base station in a designated region, and obtaining a feature data set; performing classification processing on the feature data set according to the resource input data by using an AP clustering model to obtain at least one resource classification site; inputting the resource input data in the resource classification sites into a pre-trained ridge regression-optimization model to carry out resource input anomaly detection, and outputting resource input anomaly sites corresponding to the abnormal resource input data; inputting the resource derivation data in each resource input normal site into a pre-trained target evaluation model for resource derivation anomaly detection, and outputting a resource derivation anomaly site corresponding to the anomaly resource derivation data; according to the embodiment of the invention, the detection precision of the abnormal site is improved by using various clustering algorithms, regression algorithms and particle swarm training models.