247 results about "Data feed" patented technology

A system and method for predictive analysis, scenario simulation, and decision optimization is provided. The system includes a prediction management system executed on a distributed computing infrastructure, and a prediction engine configured to receive input data, including event parameters, user-defined constraints, real-time data feeds, and historical trends. The prediction engine generates predictive models using algorithms trained on historical event outcomes, assigns probability scores and confidence intervals to potential outcomes, and dynamically updates the models based on new input data. Actionable insights are generated and ranked according to predefined success criteria. A non-transitory computer-readable medium is used to store the predictive models, outcome probabilities, and actionable insights for subsequent analysis and reporting. This system facilitates enhanced decision-making by offering real-time insights and continuously refined predictions, thereby optimizing responses to complex events and scenarios.

A system for converting a source data feed schema into a canonical data product including a memory for storing computer-executable instructions and a processor for executing the instructions stored on the memory. Execution of the instructions programs the processor to perform operations that include receiving a source data feed having a source schema, identifying a plurality of data fields of the source schema, assigning a data category from a plurality of predefined data categories to each data field of the plurality of data fields, modifying the source schema based on predefined parameters, wherein the source schema is modified to match a target schema, comparing the modified source schema to the target schema, and in response to a determination that the modified source schema matches the target schema, converting the source data feed to a canonical data product having the target schema based on the assigned data categories.

The invention, which relates to the technical field of energy management, discloses a multi-target collaborative optimization prediction system and method for regional-level water-wind-light power generation power, and the system comprises a data collection module which is used for obtaining power generation power data, meteorological environment data and power grid load demand data in real time; the optimization processor is used for receiving the data fed back by the data acquisition module, and constructing a multi-target optimization model based on spatial-temporal feature extraction to generate a plurality of candidate optimization paths; the screening module is used for screening the candidate paths through a dynamic weight distribution algorithm and screening out an optimal collaborative optimization path; and the dynamic feedback module is used for carrying out online correction on the optimal collaborative optimization path in the real-time optimization process according to the power grid frequency deviation, the energy storage charge state and the meteorological abrupt change signal. The optimization processor constructs the multi-target optimization model based on the spatial-temporal characteristics, generates a plurality of candidate optimization paths and screens out the optimal path, and compared with a traditional single energy prediction and simple scheduling mode, the precision of power generation power prediction is improved.

The invention relates to the technical field of mechanical arm control, and discloses a multi-degree-of-freedom mechanical arm-based visual identification grabbing method, which comprises the following steps of: acquiring point cloud data of a target object by utilizing a depth camera, and screening the point cloud data to determine a target feature point; the target feature points are converted into mechanical arm base coordinate system pose data; solving an optimal joint angle; acquiring tail end pose data fed back by the depth camera in real time, and calculating a joint angle correction amount based on a preset formula and the tail end pose data; a control signal is output through the PID controller, and the seven-degree-of-freedom carbon fiber mechanical arm is controlled to grab a target object; and whether the seven-degree-of-freedom carbon fiber mechanical arm successfully grabs the target object or not is verified through point cloud collision detection. By implementing the method, the problems that mechanical arm visual grabbing has obvious defects in the aspects of flexibility of degree of freedom, visual perception robustness, control cooperation precision, grabbing verification reliability and the like, and high-precision and high-stability grabbing requirements in a complex environment are difficult to adapt are solved.

The invention relates to the technical field of data analysis, and provides a CAN bus waveform message analysis method, device and equipment and a medium, and the method comprises the steps: issuing an operation instruction carrying a preset operation parameter to an oscilloscope; in response to waveform data fed back by the oscilloscope, storing the waveform data as a message file in a preset format; analyzing and converting the message file according to the data head structural body identified by the oscilloscope to obtain a message array; performing time domain segmentation, normalization processing and de-noising processing on the data in the message array by using a Numpy library to obtain a message signal; and performing error frame screening on the message signal by adopting a strategy of supplementing one after five, and performing layer-by-layer analysis on the screened message signal based on a CAN protocol structure to obtain message analysis content. According to the invention, through the software design of the whole process, a universal scheme is adopted from data acquisition, storage and analysis to signal processing and message generation, so that the analysis universality of the CAN bus waveform message is effectively improved.

The invention relates to a smart home equipment control method and system based on QUIC point-to-point communication, and belongs to the technical field of smart home control, and the control method comprises the steps: receiving a natural language instruction of a user terminal, and carrying out the analysis to obtain a target equipment identifier and an operation intention description text; retrieving a pre-constructed equipment registry according to the target equipment identifier, and obtaining a corresponding cue word template and a QUIC connection address; calling an artificial intelligence model deployed locally, and outputting a structured equipment control instruction in combination with the operation intention description text and the cue word template; performing signature encryption on the structured equipment control instruction, establishing a QUIC end-to-end encryption transmission channel between the user terminal and the target equipment, and transmitting the QUIC end-to-end encryption transmission channel to the target equipment; receiving operation response data fed back by the target equipment after the target equipment verifies and executes the structured equipment control instruction; the device registry is dynamically optimized based on the operational response data. According to the invention, the risk of cloud service privacy leakage can be reduced, and the data security of the smart home system is improved.

Some embodiments of the present application include obtaining a trained machine learning model that was trained using training data. Production data may be obtained from a data feed selected based on the trained machine learning model. In some embodiments, feature sets and observed results may be extracted from data output from the data feed, and one or more features or results may be masked to generate the production data. Predicted results data may be generated with the trained machine learning model based on the production data and an accuracy score for the trained machine learning model may be determined based on the predicted results data. If the accuracy score satisfies a threshold accuracy condition, the trained machine learning model may be caused to be rebuilt or the training data may be caused to be updated.

Aspects of the disclosure relate to using machine learning models to automatically prioritize and orchestrate spatial data. A computing system may generate, based on inputting scene data and spatial positioning data into a machine learning model, a prioritized context that indicates physical objects that are significant within a physical environment. The scene data may comprise images of the physical environment and the spatial positioning data may comprise an indication of states of a user in the physical environment. Based on the prioritized context meeting user criteria, generate indications associated with the prioritized context. Based on the scene data, one or more spatial anchors at which to position the one or more indications of the prioritized context within a virtual environment based on the physical environment may be generated. The virtual environment comprising the indications of the prioritized context positioned at the one or more spatial anchors may be generated.

The invention discloses a 10kV overhead line adaptive evaluation method and system for non-power-cut operation, and the method comprises the following steps: obtaining the field data of a target line, and constructing the field data into a multi-dimensional evaluation feature vector according to a preset evaluation dimension system for non-power-cut operation; inputting the multi-dimensional evaluation feature vector into a non-power-cut operation adaptability evaluation model to obtain a comprehensive evaluation score and an optimization suggestion of the target line; outputting the comprehensive evaluation score and the optimization suggestion; wherein the non-power-cut operation adaptability evaluation model is constructed by the following steps: training to obtain an initial machine learning model; simulating a preset non-power-cut operation task flow in the digital twinborn body; and performing incremental training and parameter optimization on the initial machine learning model by using operation effect data fed back after actual operation of the simulation data vector. The problems of single evaluation dimension, model stiffness and the like in the prior art can be solved.

The invention relates to the technical field of intelligent traffic and smart city waste management, and discloses a path planning method and system for a garbage transport vehicle based on multi-source data, and the method comprises the steps: generating a reference path based on historical collection and transportation data, the method comprises the following steps: performing data cleaning on pre-acquired garbage quantity data, vehicle state data, real-time traffic data, hydroelectric data and fuel consumption data, performing multi-source time sequence feature fusion anomaly detection on a cleaned data set, performing trajectory inversion on the cleaned data set, performing target constraint through a mixed integer programming model, and performing multi-source time sequence feature fusion anomaly detection on the cleaned data set. Then gradient descent parameter optimization is carried out on the initial optimization model, elastic resource scheduling is carried out on an optimized path scheme based on a large event plan library, a path instruction set is generated, dynamic re-optimization evaluation is carried out on the path instruction set based on garbage amount change and traffic condition data fed back in real time, and an updated path is generated; according to the invention, the path planning efficiency of the garbage transport vehicle based on the multi-source data can be improved.

A system for automated real-time publication processing may comprise a data collection module configured to automatically gather data from multiple external sources. A data analysis module may be configured to process the gathered data using artificial intelligence models. A data visualization module may be configured to generate interactive visual representations of the processed data. An update control module may be configured to automatically update published content and maintain version history with timestamps. The data collection module may utilize application programming interfaces and web scraping tools to gather data from government databases and real-time data feeds. The data analysis module may employ machine learning libraries to process and analyze the collected data. The data visualization module may use visualization tools to create interactive charts and graphs. The update control module may use Git-based version management and automated scheduling scripts to implement updates and record modification dates.

An integrated system for generating innovative solutions is disclosed. The system comprises a literature review AI agent, a knowledge graph, and a TRIZ Module. The AI agent continuously analyzes diverse information sources, feeding data into the knowledge graph. The knowledge graph organizes and connects information, identifying patterns and relationships. The TRIZ Module interacts with both components to identify contradictions and generate innovative solutions. This system accelerates innovation by processing vast amounts of information, recognizing cross-disciplinary patterns, and applying systematic problem-solving techniques.

A multi-stage deep learning method is provided, comprising training a deep learning network using a set of training pairs interchangeably including input data from a first noisy dataset with a first noise level and target data from a second noisy dataset with a second noise level, and input data from the second noisy dataset and target data from the first noisy dataset; generating an ultra -low noise data equivalent based on a low noise data fed into the trained deep learning network; and retraining the deep learning network on the set of training pairs using the target data of the set of training pairs in a first retraining step, and using the ultra-low noise data equivalent as target data in a second retraining step.

A computing system for applying post-authorization modeling tools to a payment transaction for enhancing a decision intelligence (DI) score is disclosed. The computing system is configured to: (i) build a pre-authorization and a post-authorization model to analyze backward velocities and forward velocities; (ii) receive an authorization message for a current transaction; (iv) input into the pre-authorization model current transaction data and the backward velocities for the current transaction to output a DI score; (v) based upon the DI score, authorize the current transaction; (vi) continuously monitor a data feed for a predefined period of time after authorizing the current transaction; (viii) update a data register to include the forward velocities for any post-authorization transactions received during the predefined period of time; (ix) update the DI score for the current transaction by inputting the forward velocities into the post-authorization model to transmit the updated DI score to the merchant.

A threat management facility for an enterprise network integrates native threat management capabilities with threat data from a cloud service provider used by the enterprise. By properly authenticating to the cloud service and mapping data feeds from the cloud service to a native threat management environment, the threat management facility can extend threat detection and management capabilities beyond endpoint-centric techniques.

The invention provides a large-model multi-agent interaction coordination system, method and server, and relates to the technical field of agent coordination control, the large-model multi-agent interaction coordination system provided by the invention comprises a user access layer, an agent service layer, a protocol layer, a capability layer and a data layer; request information can be obtained through a user access layer; the intelligent agent service layer comprises an intelligent agent dispatching center and a plurality of intelligent agents communicating with the intelligent agent dispatching center, and the plurality of intelligent agents exchange data through the protocol layer; the agent service layer carries out instantiation decomposition on the request information to obtain a subtask agent to execute a subtask and generate feedback task data; the task data fed back by each agent is summarized to obtain the feedback information corresponding to the request information, and the feedback information is displayed in the user access layer, so that the whole system can realize efficient collaboration and cooperation of multiple agents, the ability of the whole system to deal with complex tasks is improved, and the problem solving efficiency is greatly improved.

A computer-implemented method for facilitating one or more users virtually participating in a racing event, the method including: receiving, by one or more processors, a data feed from the event; processing, by the one or more processors, the data feed to generate a multi-dimensional virtual environment which substantially replicates the physical environment of the event, the multi-dimensional virtual environment including: virtualized representations of each participant in the event, wherein each of the virtualized representations of the participants is adapted to move inside the multi-dimensional virtual environment according to physical movements of the corresponding participant during the event, and one or more avatars corresponding with the one or more users, communicating, by the one or more processors, with computer hardware associated with the one or more users to: enable a display associated with the computer hardware to present, from a viewpoint associated with the user's avatar, the multi-dimensional virtual environment to the user, including the virtualized representations and any movement of the virtualized representations, thereby enabling the user to visualise the racing event as time passes, and enable, based on user instructions, the user's avatar to navigate the race path, thereby enabling the user to participate in the racing event and compete against the participants.

A method for safeguarding data in dynamic relational order management involves receiving a data feed and a dynamic order with various order attributes, including a protected dataset and an unprotected dataset. The protected dataset, containing a request type and a reserve execution threshold, is obfuscated from display on a respondent system. Instructions are transmitted to the respondent system to present a proposal request dataset for executing the dynamic order, comprising the unprotected dataset and the data feed. A proposal response dataset is received from the respondent system, including first and second execution values. Adjusted values are generated based on the received data, and an execution action is performed when the adjusted execution values meet the adjusted reserve execution threshold.

A system and method for processing a claim includes a consumer opt-in module, a consumer verification module, a policy, a consumer electronic health record, an electronic data feed, a code catalogue comprising a first code and a second code, a notification module, an application programming interface configured to facilitate access to data of the consumer electronic health record, a large language model, and a database configured to receive queries, updates, and validations from the large language model. The system and method may further include an input form, a claim manager module, and a code library. An error detection module may be implemented to monitor the electronic data feed, identify errors, and release an error notification; and a control module configured to receive the error notification. The system and method may also classify a claim as payable or potentially payable.

The invention relates to the technical field of data one-way transmission, and provides a state feedback ferry-based one-way data transmission method and system. Two one-way physical transmission channels are arranged between a sending agent and a receiving agent; the sending agent controls the retransmission of the data based on the maximum serial number of the successfully transmitted continuous frame data fed back by the receiving agent through the reverse state feedback channel; the reverse state feedback channel is a physical one-way import device which is independent of reverse transmission of the main physical one-way transmission channel; the reverse state feedback channel limits the channel transmission capacity based on the size of the state feedback file of the maximum serial number. Under the architecture constraint of physical one-way transmission, the state feedback of the receiving end and the intelligent retransmission of the sending end are indirectly realized through the innovative design of an application layer; on the premise of not sacrificing absolute safety brought by physical one-way isolation, the technical prejudice can be broken through, and the reliability problem of data transmission is solved.

The application relates to the chip technical field and discloses a partition unit, a partition, a chip, a network-on-chip implementation method and a medium. The partition unit comprises the following steps: obtaining an operation type and an access address corresponding to a memory access request through a secondary cache, and forwarding the memory access request to a control module of a directory corresponding to the access address when the operation type is a partial write operation; writing request data corresponding to the memory access request into a small-capacity cache through the control module, reading a target partition unit corresponding to the partition unit from a state recording module, generating a listening request according to the memory access request and sending the listening request to the target partition unit, receiving listening data fed back by the target partition unit, merging the listening data and the request data to generate complete data, and writing the complete data into a memory controller. Hardware support for cache consistency can be provided in an artificial intelligence chip with a multi-core architecture, and a network-on-chip implementation scheme supporting cache consistency is provided.

The application discloses a kind of three-phase load imbalance monitoring alarm method.The method comprises: obtaining the current data, power data and appeal work order data of target area at multiple sampling time points;According to the current data and power data, determine the three-phase load imbalance type of target area;According to three-phase load imbalance type and appeal work order data, determine whether to send risk alarm to target area.The technical scheme provided by the embodiment of the application obtains the current data and power data of multiple sampling time points in the target area, thereby obtaining the working condition of the distribution transformer in the target area at multiple sampling time points, and then determining the three-phase load imbalance type of the target area.Combined with the appeal work order data fed back by the actual experience of users in the target area, the power supply condition in the target area can be judged more accurately, and the target area needing to send risk alarm is prompted, so that the technical effect of improving the management efficiency of power grid and the satisfaction of users is realized.

In accordance with some embodiments, systems, apparatus, interfaces, methods, and articles of manufacture are provided for providing information incorporating additional data feeds, creating common arrangements, and improving performance in a virtual meeting. In some embodiments, a video conferencing system hosts a customized video conferencing and includes video conference settings data, participant display device data, supplemental data feed data, and processing instructions. The video conferencing system may identify (based on the video conference settings data) a number of data feeds for display on a display screen of each participant in a video conference and (based on the participant display device data) a screen specification for each display screen of each participant. The system may then compute an arrangement for the number of data feeds that fits within an available display area.

Systems and methods related to financial trading are provided. More specifically, some embodiments relate to systems and methods for electronic trading using market data channels which users can subscribe. Various embodiments of the present technology can provide a suite of devices that are designed to actively modify market data at the intake point (co-location facility) in order to optimally disseminate only relevant information to various applications. These filtered market data channels can then be accessed by trading systems through various subscription models. Various embodiments allow for any type of channel that alters the natural or pure market data feed to produce different data flows and other signals (e.g., triggers, synthetic prices, etc.)

The invention discloses a port container scheduling system and method based on GRASP and SAC. The system comprises a data acquisition module which is used for acquiring real-time data from port equipment and an environment sensor and preprocessing the real-time data; the optimization algorithm module is used for receiving the data output by the data acquisition module and generating a scheduling scheme, or receiving abnormal data fed back by the real-time monitoring module, automatically starting a GRASP algorithm and / or a SAC algorithm and regenerating the scheduling scheme; the task scheduling module is used for receiving the scheduling scheme and executing and adjusting specific task distribution and equipment scheduling operation; and the real-time monitoring module is used for monitoring the equipment state and the task execution condition and transmitting abnormal information to the optimization algorithm module. According to the method, the optimization algorithm modules are constructed by combining the GRASP and the SAC algorithm, and the modules are clear in division of labor and are in close cooperation, so that the whole scheduling system forms an efficient and cooperative whole, and the overall efficiency and stability of the scheduling system are improved.

Methods and systems for deploying intrusion detection system (IDS) policies to IDS programs are disclosed. Each IDS instance can monitor a data feed (e.g., comprising computer network traffic) in accordance with a set of “signatures” or “rules” associated with its policy, and can issue alerts if any elements of that network traffic match those signatures or rules. An intrusion signature management module can receive IDS signatures from one or more signature sources and store those signatures in a filesystem. The intrusion signature management module can produce rule files based on these IDS signatures, e.g., containing subsets of the received IDS signatures. These rule files can be provided to a version control server, and can later be accessed by an orchestration module. The orchestration module can deploy these rule files to their respective IDS programs, enabling those IDS programs to monitor their respective data feeds in accordance with the rule files.

A quantum computing platform may train, using historical workload information, a container configuration generation model. The computing platform may receive, from a workload processing system, a data feed indicating current workload information. The computing platform may input, into the container configuration generation model, the current workload information, which may cause the container configuration generation model to produce a container configuration output, where the container configuration output may be an optimal batch configuration for processing the data feed, and where the optimal batch configuration may be a configuration that optimizes between computing resources and processing speed. The computing platform may send, to the workload processing system, the container configuration output and one or more commands directing the workload processing system to process the data feed using the optimal batch configuration, which may cause the workload processing system to process the data feed using the optimal batch configuration.

A system for virtually broadcasting from within a virtual environment, comprising a server computer system. The system implements a data exchange management module configured to manage data exchange between client devices and at least one virtual environment comprising a virtual broadcasting camera positioned within the virtual environment and configured to capture multimedia streams of a virtual multimedia streams source from within the virtual environment. The system is configured to receive live feed data captured by at least one camera from at least one client device and broadcast the multimedia streams to the client device based on data exchange management. The broadcasted multimedia streams are configured to be displayed to corresponding user graphical representations generated from a user live data feed from at least one client device. The data exchange management comprises analyzing the incoming multimedia streams and assessing the forwarding of outbound multimedia streams based on the analyzing.

The invention discloses a data caching method and device, electronic equipment and a storage medium, and relates to the technical field of communication. The data caching method comprises the following steps: acquiring identification information of each data transmission instruction sent by a main port, and performing circular identification mapping on the identification information to obtain target identification information corresponding to each data transmission instruction; sending each data transmission instruction to each slave port according to a preset interleaving rule based on the target identification information, so that the slave port obtains return data according to the data transmission instruction; and obtaining return data fed back by the slave port, determining a target position of the return data in the shared memory according to the target identification information, and storing the return data according to the target position. According to the embodiment of the invention, the returned data of different channels are stored through the shared memory, and a cache space does not need to be set for each slave port, so that the required cache space is reduced, the consumption of the memory is reduced, and the cost of the cache space is reduced.

Described herein are systems and methods for generating and transmitting media data feeds location-based privacy settings. Embodiments generate, store, and reference location-based privacy settings that instruct the computing device to generate obfuscations in the media data. The obfuscations may include computer-generated or user gesture-generated obfuscation regions that instruct the computing device to apply the obfuscations to portions of the video feed. The computing device may be pre-configured to recognize certain objects or regions (or portions thereof) and remove, blur, or substitute them from the live video stream or 3D data according to privacy settings. The privacy settings may be relative to the location in which the user and computing device are situated. In operation, the computing device may determine the location and then apply the location-specific privacy settings to obfuscate a portion of the video feed while being generated and transmitted.