1513 results about "Data exchange" patented technology

A federated distributed computational system enables secure oncological therapy optimization through robotic integration. The system establishes a distributed graph architecture with secure communication channels connecting computational nodes, implementing encryption protocols for cross-institutional data exchange. Each node contains processing capabilities for fluorescence-guided imaging, uncertainty quantification, and expert knowledge integration while maintaining hierarchical knowledge graphs of oncological biomarkers, interventions, and outcomes. The system coordinates domain-specific knowledge through token-space communication and implements an advanced robotic integration system for surgical interventions using spatiotemporal tumor mapping, multi-modal fluorescence imaging, surgical robot coordination, and space-time stabilized mesh management. Key capabilities include wavelength-specific multi-modal fluorescence detection, combined epistemic and aleatoric uncertainty estimation, tensor-based data integration with adaptive dimensionality control, and light cone search for adaptive treatment optimization—all while maintaining strict privacy controls.

A federated distributed computational system enables secure, privacy-preserving biological data analysis and engineering through interconnected nodes coordinated in a distributed graph architecture. A federation manager allocates resources, manages data flow and lineage, establishes privacy boundaries, and maintains cross-institutional knowledge relationships. Each node contains a processing unit for biological data analysis, privacy preservation protocols for secure multi-party computation, a knowledge graph structure with supporting data stores, and encrypted network connections. The federation manager enforces all computation and data exchange through secure channels while maintaining privacy, security, and contractual boundaries. This architecture enables research institutions to collaborate on complex biological analyses without compromising sensitive data, facilitating breakthrough discoveries through shared computational resources while maintaining strict data privacy and security controls.

A federated distributed computational system enables secure oncological therapy optimization through multi-expert integration and advanced uncertainty quantification. The system implements a multi-expert integration framework that coordinates domain-specific knowledge through token-space communication for precision oncological treatment, while maintaining secure cross-institutional data exchange. The architecture coordinates multi-scale spatiotemporal synchronization across computational nodes, with each node containing local processing capabilities for fluorescence-guided imaging, uncertainty quantification, and expert knowledge integration. Through a distributed graph architecture, the system enables advanced fluorescence imaging with wavelength-specific targeting, multi-level uncertainty estimation combining epistemic and aleatoric approaches, and multi-scale tensor-based integration with adaptive dimensionality control. The system implements light cone search and planning for adaptive treatment strategy optimization, enabling medical institutions and research organizations to collaborate on complex oncological therapy projects while maintaining strict data privacy controls.

A federated distributed computational system enables secure biological data analysis and genomic medicine through hybrid simulation capabilities. The system implements a hybrid simulation orchestrator that coordinates classical numerical simulations with machine learning models for biological system analysis, while maintaining secure cross-institutional data exchange. The architecture coordinates multi-scale spatiotemporal synchronization across computational nodes, with each node containing local processing capabilities for biological data analysis and privacy preservation protocols. The system implements cellular machinery assembly analysis, real-time patient data integration, and multi-modal image integration with spatiotemporal health data annotation. Through a distributed graph architecture, the system enables cross-species genetic analysis, environmental response modeling, and multi-scale tensor-based data integration with adaptive dimensionality control. The system implements real-time therapeutic response prediction through multi-modal data analysis, enabling research institutions to collaborate on complex biological analyses while maintaining strict data privacy controls.

The invention provides an electronic information data association method and system based on the Internet of Things. The method comprises the steps that a parallel processing architecture is adopted to execute rapid protocol conversion on a high-priority data packet, data recombination is directly carried out through a pre-compiled conversion rule template, a complex format verification link is skipped, and the integrity and format correctness of the converted data packet are determined; response time and error rate statistical information in the data transmission process are obtained, protocol conversion rules and scheduling strategies are optimized through a feedback mechanism, and if the success rate of certain protocol conversion is lower than a standard value, corresponding mapping rules and verification algorithms are updated; and carrying out standardized packaging on all converted data by adopting a unified data exchange standard, adding an equipment identifier, a timestamp and a data type label, establishing a cross-protocol general data format, and carrying out final distribution after judging whether a data packet meets a standard format requirement.

The invention discloses an urban safety risk assessment method and system based on big data, and relates to the technical field of big data, and the method comprises the steps: constructing a multi-source data collection network, and obtaining data from a government department database, Internet of Things equipment, a social media platform and a traffic monitoring system in real time; preprocessing the collected multi-source data, wherein the preprocessing comprises data cleaning, format standardization, unstructured data semantic analysis and sentiment analysis; a cross-department data security sharing mechanism is established, and the traceability and security of data exchange are ensured through a block chain technology; constructing a dynamic risk assessment model, analyzing multi-source data relevance based on a deep learning algorithm, and dynamically adjusting the weight of each risk factor; and generating a visual risk assessment report, and pushing the visual risk assessment report to related departments in real time through an early warning system. According to the invention, through multi-technology fusion and a dynamic optimization mechanism, the accuracy, real-time performance and cooperation efficiency of urban safety risk assessment are significantly improved.

Systems, apparatus, and methods of managing access to private data via tokens are disclosed. The disclosed techniques provide for constructing digital tokens that represent a right-to-access private data where the tokens can be managed as individual objects. Further, such digital access tokens (DATs) can be recorded on a notarized ledger, a blockchain for example. Additionally, the rights-to-access can be embodied as a non-fungible token (NFT), which could further include support for establishing homomorphic encryption workspaces in which private data can be accessed or manipulated without exposing the private data.

Systems, apparatus, and methods of managing access to private data via tokens are disclosed. The disclosed techniques provide for constructing digital tokens that represent a right-to-access private data where the tokens can be managed as individual objects. Further, such digital access tokens (DATs) can be recorded on a notarized ledger, a blockchain for example. Additionally, the rights-to-access can be embodied as a non-fungible token (NFT), which could further include support for establishing homomorphic encryption workspaces in which private data can be accessed or manipulated without exposing the private data.

The invention relates to the technical field of network and information security, in particular to a zero-trust multi-party security data exchange method, which comprises the following steps of: generating a zero-trust token and a capability authorization bill and constructing context description data; authentication encryption is performed on the plaintext fragment, attribute-based encryption is performed on the data one-time key, and a policy bearing ciphertext container is assembled; in the trusted execution environment, authentication decryption is completed through a one-time secret key of data recovery through joint challenge and threshold deblocking, or strategy migration and transfer are achieved through proxy re-encryption; and aggregating the decryption event and the forwarding event by vector commitment, generating a time anchor, and mapping the time anchor into a next round of random base. According to the invention, fine-grained authorization of the key layer, no plaintext transfer, event-level verifiable auditing and rapid revocation are realized.

The invention discloses a transistor high-power electromagnetic heat model optimization system based on deep learning, and relates to the technical field of electromagnetic heat. Comprising an input module, a deep learning module, a global optimization module, an online adaptive module and a real-time simulation module. The input module obtains various key parameters and constructs a high-dimensional input space; the deep learning module constructs a deep learning model by embedding a physical constraint and uncertainty quantization mechanism; the global optimization module is used for carrying out global search on design parameters, rapidly evaluating a target function by utilizing an agent model, and searching a Pareto optimal solution in a design parameter space; the online adaptive module is used for drift detection and updating; the real-time simulation module simulates an electromagnetic field and a thermal field in real time, and data exchange ensures timely synchronization of boundary data through dynamic scheduling and load balancing; all the modules cooperate with one another through data and feedback, and a complete, closed-loop and continuously self-adaptive updating optimization system is achieved.

The invention discloses a data exchange system for performing real-time secure communication with an intranet system, and relates to the technical field of network data security. The system comprises a network environment identification module, a challenge authentication module, a hardware key binding module, a data communication module, an abnormal response module, a strategy updating module and a visual monitoring and log module. According to the invention, by introducing the trust map evaluation module, map modeling is carried out on the characteristics of the equipment in the historical operation process, the rationality of the current operation environment of the system is judged based on the map coincidence evaluation result, the communication module is allowed to operate only when the evaluation result meets the condition, and a judgment mechanism based on the historical trusted behavior is formed; and the prevention and control capability of the system on gradual-change attacks and behavior counterfeit is enhanced.

Various embodiments described herein relate to systems, methods, and non-transitory computer-readable media structured to perform server-to-device secure data exchange using a device access token. In an embodiment, a smart device receives, from a requestor entity provided to the smart device, an account data provisioning request for an account. Based on the account data provisioning request, an account identifier for the account is determined. In some arrangements, the account identifier comprises or is associated with a device access token. Based on the device access token, a data element associated with the account is determined. In some embodiments, the data element is accessible to the requestor entity only if it is not access-restricted based on the device access token. Based on the data element, an executable graphic rendering instruction is generated. The executable graphic rendering instruction is executed, which includes generating and displaying, on a user interface of the smart device, a dynamic account status indicator relating to the account.

A federated learning system (100) for data protection in data sharing and collaboration, consisting of: a module for data acquisition and local preprocessing that is configured to clean, normalize and standardize local data sets at each participating node without transferring raw data externally; a local model training module configured to train a machine learning model on the pre-processed local dataset; a secure model update and encryption module configured to encrypt and secure model parameters or updates before transmission using privacy protection techniques; a federated aggregation and coordination module configured to aggregate encrypted updates from multiple participating nodes into a global model; a module for monitoring and ensuring data protection compliance, configured to enforce data protection budgets and audit protocols and to ensure compliance with data protection regulations; a performance optimization and resource management module configured to optimize communication, computation, and resource utilization across all nodes; and a module for global model delivery and feedback, configured to redistribute the aggregated global model to participants and integrate performance feedback for iterative improvements.

The invention relates to the technical field of edge computing, and discloses an intelligent edge computing co-processing system based on an integrated circuit, which comprises a heterogeneous computing cluster module, a hardware computing unit set, a multi-core control processor based on RISC-V, a programmable pulse tensor computing array and a reconfigurable engine oriented to streaming processing, according to the intelligent edge computing cooperative processing system based on the integrated circuit, zero-delay data exchange is realized through silicon intermediate layer integration of the heterogeneous computing cluster module and a snakelike data channel, and traditional bus arbitration delay is eliminated through real-time operation code analysis and optimal optical communication path mapping of the hardware task routing matrix (TRF) module; the priority path distribution of the task scheduling subsystem is synchronously coordinated with the time-sensitive task, so that the collaborative efficiency of the computing unit is improved in multiple dimensions, the non-blocking transmission of the high-priority task is ensured, and the effect of enhancing the overall processing capability and response speed of the intelligent edge computing is achieved.

The invention discloses a hydraulic fracture monitoring system and method based on an underground micro-seismic sensor network, and belongs to the field of coal mining, and the system comprises a plurality of micro-seismic sensors which are used for collecting micro-seismic signals generated by rock fracture; the plurality of data acquisition substations are used for receiving and processing the micro-seismic signals; the data transmission substation is used for converting the micro-seismic signal processed by the data acquisition substation into an optical signal; the micro-seismic server performs micro-seismic event analysis according to the optical signal; the mining network switch is connected with the data transmission substation and the micro-seismic server and is used for network data exchange; the in-mine ring main unit is connected with the mining network switch and the micro-seismic server to form a communication network of the system; in order to solve the problem that hydraulic fracture detection precision is low due to the fact that micro-seismic signals generated by hydraulic fracture and coal mining activities are difficult to accurately distinguish in a complex underground environment, the hydraulic fracture detection method and device distinguish the micro-seismic signals generated by hydraulic fracture and coal mining activities by dividing a fracture area and a mining area, and the real-time monitoring precision of hydraulic fracture expansion is improved.

Disclosed is a fraud-related gang incident recognition system and method based on intelligence sharing and graph calculation, and a related device. The solution mainly comprises an intelligence sharing platform and an incident model based on graph calculation. The intelligence sharing platform integrates a plurality of trained recognition models, establishes a model intelligence sharing system, and summarizes multivariate information of each model in real time. The incident model based on graph calculation is configured to perform data exchange with the intelligence sharing platform. The incident model based on graph calculation is configured to classify nodes based on a graph neural network, and perform analysis on same on the basis of economic characteristics and social characteristics, to construct a social network graph of the incident, further identify overlapping gang structures on the basis of the social network graph, and transmit the overlapping gang structures to the intelligence sharing platform for recognition processing. In the solution of the present invention, gang organizations in social networks can be effectively discovered and identified by combining a graph calculation method of node attributes and a network topology structure and by using an intelligence sharing platform.

The various embodiments herein provide a system and method for networked digital twins with autonomous collaborative decision-making. The system comprises a Digital Twin Engine for real-time data acquisition, model synthesis, and simulation, an AI Module for advanced data analysis, an autonomous collaborative decision-making module for optimized decision-making, a communication layer for secure data exchange, and supporting modules for coordination, storage, security, and user interaction. The method for generating and deploying digital twins comprises data collection, transmission, preprocessing, model synthesis, simulation, validation, and deployment. The method for networking and collaboration comprises AI-based data processing, complex event processing, autonomous decision-making, task distribution, decision communication, real-time monitoring, and continuous improvement. This system enhances operational efficiency, scalability, and security, reducing the need for human intervention and providing a comprehensive management solution for complex systems.

The invention belongs to the technical field of communication, and particularly relates to an NFC (Near Field Communication) encrypted IMS (IP Multimedia Subsystem) server security data exchange method, which comprises the following steps of: in response to a near field communication connection event, acquiring an original service data message of service equipment to be opened and physical environment data monitored when the event occurs, forming a seed data set, executing Hash operation to generate an initial data fingerprint, and sending the initial data fingerprint to a server; and generating a symmetric session key through a key derivation algorithm by combining a device identifier in the original service data message, so as to encrypt the original service data message, packaging an encrypted data packet and the initial data fingerprint into a transmission data packet, sending the transmission data packet to an IMS server, reconstructing the session key by the server based on expected service parameters stored locally, and sending the session key to the IMS server. According to the method, decryption verification of the encrypted data packet is carried out, and service opening is executed after the verification is passed, so that deep binding of an encryption process and data integrity verification is realized, and the security of data exchange and the system processing efficiency are improved.

The invention relates to the technical field of photovoltaic power adjustment, and discloses a photovoltaic power automatic adjustment method and system. The method comprises the steps of collecting real-time parameters of an inverter through distributed communication, performing multi-dimensional evaluation sorting based on equipment efficiency, load rate and operation time, executing adaptive power distribution fusing edge calculation and cloud optimization, generating standardized instruction time-sharing issuing, and storing control logic by using a block chain. And an encrypted link is established to realize bidirectional data interaction between the power station and the dispatching system to form a closed-loop control system. According to the invention, high-efficiency, precise and reliable dynamic power adjustment of the inverter level is realized.

The invention relates to an optical data network (10-1) for connecting a plurality of data network nodes (N1-1, N2-1, N3-1, N4-1). The optical data network (10-1) comprises: i) the plurality of data network nodes (N1-1, N2-1, N3-1, N4-1), the data (99) comprising data packets (99p), wherein each data network node (N1-1, N2-1, N3-1, N4-1) is provided with a network interface (Nl); and ii) a data connection network (100-1) comprising at least one data switch (SW) and a plurality of optical connections (50) for allowing establishment of data links (DL1, DL2) between pairs of said plurality of data network nodes (N1-1, N2-1, N3-1, N4-1). At least one of the at least one data switch (SW) is a smart data switch (SSW) comprising at least one packet switch (PS, EPS) and at least one circuit switch (CS, OCS), At least two network interfaces are smart network interfaces (SN, SNC) comprising a data classifier (25) configured for classifying the data packets (99p) into at least two traffic classes including first traffic class (D1) and a second traffic class (D2) in accordance with a classification scheme. The smart data switch (SSW) and the network interfaces (SN, SNC) are configured to route the data packets (99p) of the first traffic class (D1) to the packet switch (PS, EPS) and to route the data packets (99p) of the second traffic class (D2) to the circuit switch (CS, OCS).

The embodiment disclose a wearable augmented reality eyewear system including a frame supporting left and right transparent lenses. A plurality of outward-facing cameras mounted on the frame have overlapping fields of view for capturing real-time images of the environment. A plurality of inward-facing cameras integrated in the frame or lenses detect pupil size, pupil dilation, and gaze direction using infrared imaging. A digital processor analyzes gaze direction and fixation based on virtual grid coordinates, initiates an object or person recognition routine using images from the outward-facing cameras, and compares detected features with records in a database. At least one lens includes an AR projection system embedded therein and configured to superimpose data about the recognized object or person in the user's field of view. An audio speaker positioned near the user's ear outputs related audio. A wireless communication module enables real-time data exchange with a cloud-based platform.

A federated distributed computational system enables secure drug discovery and resistance tracking through hybrid simulation capabilities. The system implements a hybrid simulation orchestrator that coordinates molecular dynamics simulations with machine learning models for drug discovery analysis, while maintaining secure cross-institutional data exchange. The architecture coordinates multi-scale spatiotemporal synchronization across computational nodes, with each node containing local processing capabilities for molecular dynamics simulation and resistance pattern detection. Through a distributed graph architecture, the system enables real-world clinical data integration, resistance evolution tracking, and multi-scale tensor-based analysis with adaptive dimensionality control. The system implements real-time drug response prediction through multi-modal data analysis, enabling pharmaceutical companies and research institutions to collaborate on complex drug discovery projects while maintaining strict data privacy controls.

System and methods are provided for automated SKU management. Embodiments include a user interface for receiving diverse catalog files, a Catalog Transformation module, a Real-Time Data Mesh (RTDM) module, a Master Data Governance (MDG) module, a Global Data Repository (GDR), and a Search Platform. The Catalog Transformation module, through iterative learning, transforms catalog files to a standard format and predicts categorization and attribute mapping. The RTDM module is configured to perform real-time data exchange. The MDG module validates the transformed catalogs. The GDR stores validated catalogs. Embodiments can include a Dynamic SKU Creation module and a Global Pricing Engine for real-time pricing. Embodiments improve data accuracy and SKU management, facilitating integrated order processing and fulfillment.

The invention relates to the technical field of data processing, in particular to an HTML (Hypertext Markup Language)-based webpage word cutting annotation generation method, system and equipment, and aims to solve the problems of low storage efficiency, poor dynamic webpage adaptability, lack of fault tolerance and insufficient cross-browser compatibility of an existing word cutting annotation method. The method comprises the steps of capturing a selected area; obtaining DOM node path data and text offset, and generating positioning data; recursively storing the path data to generate a unique fingerprint identifier; storing the fingerprint data as historical fingerprint data in a JSON format; performing matching and positioning based on the historical fingerprint data; and mapping information in the historical fingerprint data to an HTML page to realize bidirectional rendering. According to the method, the label name, the class name and the hierarchical relationship of the DOM node are recorded through the node path to construct the fingerprint identifier, and cross-platform data exchange is realized through the JSON structure, so that webpage labeling which is efficient, accurate, high in fault tolerance and adaptive to a dynamic page is realized.

The invention provides a multi-party data collaborative exchange method, system and device, a medium and a product, and belongs to the technical field of data information processing, and the method comprises the steps: in a data exchange process, after identity authentication of participants of data exchange is passed in a trusted space, carrying out the dynamic verification of the access authority of the participants based on the real-time attributes of the participants; under the condition that the dynamic verification is passed, executing data exchange in the trusted space to obtain a data exchange result; sending the data exchange result to a data decryption party corresponding to the data user, so that the data decryption party decrypts the data exchange result; wherein the real-time attributes of the participants comprise real-time environment attributes, behavior attributes of the participants and static attributes of the participants. When the access permission is verified, transition from role-based access control to behavior-based access control is realized on the basis of dynamic combination of multi-dimensional attributes, and dynamic control on the access permission is realized on the aspect of finer granularity.

A computer-aided system and associated method for automated building design includes receiving input parameters and generating a three-dimensional parametric computer model of a building frame and populating the three-dimensional computer building model with generic and manufacturer-specific products by accessing internal and external data sources. The populated computer model undergoes real-time simulation to analyze regulatory compliance, verify engineering requirements including load calculations, and evaluate cost considerations. Based on simulation results, the method generates output documents including requests for proposals (RFP documents) for contractors, requests for quotations (RFQs) for vendors, and regulatory compliance documentation. These documents are transmitted to respective stakeholders through a secure data exchange protocol. The method further includes receiving responses to the generated RFP documents / RFQs.

The invention discloses a logistics full-process optimization method based on multimodal transport digital development, and belongs to the field of logistics, the logistics full-process optimization method based on multimodal transport digital development comprises the following steps: formulating a unified data exchange standard, and defining a standardized digital format for each type of documents; on the basis of a unified data exchange standard, a unique digital main document which runs through the whole transportation process is created for goods transported each time, and the digital main document serves as a unique digital certificate of the ownership of the goods and a transportation contract; the method has the beneficial effects that a trusted data closed loop capable of automatically circulating, checking and responding to exceptions is constructed by formulating a unified data exchange standard, creating a digital main document running through the whole process, constructing a cloud collaboration platform and embedding an intelligent rule engine; therefore, a traditional mode of multimodal transport depending on manual coordination is converted into an efficient, automatic and transparent digital operation mode.

The invention relates to the technical field of medical information, and particularly discloses an ERP (Enterprise Resource Planning) integration-based medicine transaction data synchronization system, which comprises a data acquisition module, a mapping analysis module, a data fusion module, a trend analysis module and a center console module. According to the scheme, the multi-dimensional feature space is constructed, the field structures in different service systems are identified and mapped to the uniform target field set to construct the dynamic mapping table, and the adaptability to different service systems is enhanced; a dynamic updating mechanism based on event driving is designed, complex business logic is flexibly handled, the system load is reduced, the system operation efficiency is improved, the compliance of a business process is ensured through cooperation of a rule engine, and the problem of data conflict possibly occurring in the data synchronization process of multiple business departments is solved; and a center console is arranged to monitor efficient circulation of medicine transaction data, so that the stability and safety of data exchange are ensured, a reliable tracing basis is provided for medicine supervision, and subsequent analysis and maintenance are facilitated.

The invention discloses a nursing medicine education system based on the Internet, and relates to the field of computer application technology and education management, and the system comprises a theory learning module which is used for achieving the online teaching and personalized learning pushing of nursing theory knowledge, the nursing skill training module is used for training and evaluating the standardized nursing operation ability of students, the virtual simulation practical training module is used for providing an immersive virtual clinical training environment, and the structured nursing document training module is used for improving the ability of the students to write standard nursing documents. The intelligent evaluation module is used for carrying out automatic, multi-dimensional and structured comprehensive evaluation on the learning and training process of students, and the system integration interface module is used for realizing data exchange and interaction between the teaching platform and an existing information system of a hospital. The system has the advantages of complete functions, closed-loop data and accurate intelligent evaluation, and can effectively improve the standardization, practicability and intelligent level of nursing education.

The invention relates to the technical field of fire-fighting simulation, and discloses a fire-fighting fire dynamic simulation system based on multi-physics field coupling. The system collects temperature field distribution data, smoke concentration gradient data, airflow velocity field data and building structure heat conduction parameters of a fire scene; establishing a bidirectional coupling model of a temperature field and a smoke diffusion field, realizing dynamic correction of a smoke convection effect by a temperature gradient through real-time data exchange, constructing a correlation model of an airflow velocity field and a heat conduction parameter of a building structure, and adjusting a velocity field vortex coefficient according to heat flow intensity; integrating the bidirectional coupling model and the correlation model to form a multi-physical field joint calculation framework, and propelling a simulation process by adopting a discrete time slicing mode; and outputting a three-dimensional dynamic simulation map including a temperature field evolution track, a smoke diffusion path and an airflow disturbance range. The system can accurately restore the fire scene multi-physics field synergistic effect process, and provides effective support for fire rescue decision and building fire protection design.