619 results about "Time based" patented technology

An example operation may include one or more of executing a waiting period of time within a software application being accessed by a user, executing an animation via the software application during the waiting period, determining a result of the software application being accessed by the user, determining additional time to add to the waiting period of time based on the result, via the software application, executing the waiting period with the additional time, augmenting the animation based on the additional time to add to the waiting period, via the software application, and executing the augmented animation via the software application during the additional time. At least one portion of the example operation: integrates with an artificial intelligence (AI) chatbot, interacts with the AI chatbot, is performed by the AI chatbot, and / or is associated with an AI model.

The invention relates to the technical field of transformers, and provides a transformer load capacity prediction method and device, equipment and a storage medium, and the method comprises the steps: obtaining current data, winding temperature data, oil temperature data, environment temperature data and historical load records of a target transformer; calculating a temperature rise correction value based on the winding temperature data and the oil temperature data; after the temperature rise change rate in unit time is calculated through the current data, the environment temperature data and the temperature rise correction value, time sequence matching analysis is carried out on the temperature rise change rate and historical load records, after the load capacity change trend is obtained, comparative analysis is carried out on the load capacity change trend and the historical load records, and a load capacity prediction result is generated. By utilizing collaborative analysis and heat conduction characteristic calculation of multi-source data and comprehensively constructing a time delay interval and a load capacity evaluation method, the precision and applicability of transformer load capacity prediction are improved, and the problem that the prediction precision is insufficient due to the fact that operation data and environment data of the transformer cannot be fully fused during multi-source data processing is solved.

The invention discloses a logging-while-drilling reservoir parameter dynamic prediction method based on double attention convolution LSTM, and the method comprises the steps: obtaining logging-while-drilling data and drilling data in real time, and carrying out the preprocessing of the data; establishing a DTW dynamic time window model based on a gradual transition strategy, and adaptively adjusting the length of an input sequence according to the stratum change speed; a double attention convolution LSTM model is combined with the DTW dynamic time window model to establish a feature-time double attention mechanism, and two dimensions of features and time are adaptively fused based on the convolution LSTM; setting a buffer area, storing data and controlling data quality; setting an online increment fine tuning strategy; and performing instance training, and performing multi-angle evaluation on the performance of the double attention convolution LSTM model by adopting multiple indexes. According to the scheme, the influence of features and time on the prediction accuracy is fully considered, and the prediction accuracy is improved.

A system including a computing device configured to receive a time-based service record, generate a structured metadata object for the service record, the structured metadata including a plurality of programmatically assigned descriptors selected from a configurable schema, instantiate a dual-path processing routine as a function of the programmatically assigned descriptors, retrieve a constraint profile comprising at least one temporal delivery threshold associated with the resource allocation output and the utilization performance evaluation, aggregate time-based service records over a reporting interval as a function of the structured metadata, compute, using a time-mapping module, a constraint deviation metric as a function of comparing the time-based service records and the temporal delivery threshold, and generate an output object as a function of the constraint deviation metric.

Method includes receiving a first delay time and a first timing measurement by a TMV from a first receiver at a first node. The first timing measurement is generated by comparing a first time associated with a first signal to a first local clock time. The first signal is transmitted by a transmitter at a source. The TMV receives from a second receiver at a second node in a network, a second delay time and a second timing measurement. The second timing measurement is generated by comparing a second time associated with a second signal to a second local clock time. The second signal is transmitted by the transmitter at the source. The TMV generates a correction factor time based on the first timing measurement, the first delay time, the second timing measurement, and the second delay time. The TMV transmits the correction factor time to the second node.

An autonomous futures contract orchestration platform includes a set of processors programmed with a set of non-transitory computer-readable instructions. The instructions include receiving, from a data source, an indication associated with a product that relates to an entity that purchases or sells the product. The instructions include predicting a baseline cost of purchasing or selling the product at a future point in time based on the indication. The instructions include retrieving a futures cost, at a current point in time, of a futures contract for an obligation to the purchasing or selling the product for delivery or performance of the product at the future point in time. The instructions include executing a smart contract for the futures contract based on the baseline cost and the futures cost. The instructions include orchestrating the delivery or performance of the product at the future point in time.

The invention discloses a predictive maintenance algorithm for transmission equipment, and relates to the technical field of maintenance of the transmission equipment, in particular to a roller conveying system applied to flexible materials, which is characterized by comprising the following steps: S1, arranging position triggers at key transition nodes of a roller conveyor for acquiring timestamps of the materials passing through detection points in real time, generating a unique number and a corresponding time sequence relationship for each material; and S2, standard material passing time is calculated based on the theoretical beat period, the difference between the actual time and the standard period is calculated, and a beat offset set is constructed to reflect the conveying beat deviation of the materials between the adjacent detection points. According to the method, early warning and intelligent regulation and control of flexible material conveying rhythm imbalance are achieved through rhythm offset modeling, abnormal aggregation recognition and root cause diagnosis, compression bandwidth and driving time delay are dynamically adjusted when the imbalance risk occurs, the accumulation risk is effectively relieved, and the system stability, the automation level and the operation efficiency are improved.

A method, system, and article of manufacture for modifying a queue assignment for a contact center are provided. At least one computing device determines, by solving for constraints, at least one staffing change for at least one of the first queue or the second queue, using as inputs (a) first time-based service metrics, (b) second time-based service metrics, (c) data describing eligible staffing changes, and (d) at least one predetermined constraint. The at least one staffing change is a modification to the queue assignment of a subset of the computing device instances that is predicted to improve net staffing relating to service targets selected from (a) an average speed of answer (ASA) specifying an average time for one of the computing device instances to initiate handling of a particular task after the particular task has been assigned to the relevant queue and (b) a service level specifying a percentage of tasks for which handling is initiated within a specified time frame after the tasks are assigned to the queue. The at least one staffing change can be implemented by modifying the queue assignment of the subset of the computing device instances.

In a communication method, a terminal device sends uplink data corresponding to M HARQ processes, and receives first indication information, where the first indication information indicates whether to start a DRX uplink retransmission timer corresponding to N HARQ processes in the M HARQ processes; and the terminal device starts the DRX uplink retransmission timer when the first indication information indicates to start the DRX uplink retransmission timer, and receives second indication information when the DRX uplink retransmission timer runs, where the second indication information indicates retransmission of uplink data corresponding to the N HARQ processes. The terminal device can determine, in time based on the first indication information, whether to start the DRX uplink retransmission timer. A terminal device is configured with computer instructions to perform the described method.

The invention discloses a refrigerator control method and device, a refrigerator, electronic equipment and a storage medium. The method comprises the following steps: detecting a temperature sensor fault; the current operation condition corresponding to the fault sensor is determined, a temperature adjusting function of the refrigerator under the current operation condition is matched at a cloud end and serves as a target function, the cloud end carries out fitting according to normal operation data of refrigerators of the same model to obtain temperature adjusting functions under different operation conditions, and the temperature adjusting functions are used as the target function. The temperature adjusting function is used for representing the relation between a temperature parameter and time, and the temperature parameter is the chamber temperature or the defrosting temperature; calculating target time based on the target function; and after the refrigerator is controlled to operate for the target time under the current operation condition, entering a new operation condition and re-matching the target function, and repeating the steps until the fault sensor returns to normal. The refrigerator can be accurately controlled to operate on the basis of the temperature adjusting function when the refrigerator temperature sensor breaks down.

The embodiment of the invention provides an embedded operation method and system based on preemptive multi-task scheduling, and belongs to the technical field of multi-task scheduling. The method comprises the following steps: initializing a global task priority group, a start-stop bit field group and an execution quality feedback table, and configuring parameters of a time base interrupt source; loading task parameters, and generating a task configuration table; driving each task cycle counter to accumulate through the time base interrupt source, and when the current accumulated value of the cycle counter is matched with the cycle parameter in the task configuration table and the start-stop bit field group is started, generating a ready mark graph; updating the global task priority group, determining a to-be-executed task, and completing task scheduling; and executing the to-be-executed task, calculating a task priority compensation value, and adjusting the priority value of the corresponding task in the global task priority group in the next period based on the task priority compensation value. According to the method, the defect of static scheduling accumulative errors is overcome through a dynamic priority compensation mechanism.

The invention discloses a turbine service life prediction method, system and device and a storage medium, and relates to the technical field of engines, and the method comprises the steps: fitting a stress spectrum according to the actual working rotating speed spectrum of a turbine and the relation between the rotating speed and the stress; calculating the total fatigue damage at the blade root of the turbine blade after the target working duration based on the stress spectrum; calculating the total creep damage at the blade root of the turbine blade after the target working duration based on the stress spectrum, the rotating speed spectrum of actual operation and the temperature spectrum; and predicting the comprehensive life of the turbine according to the total fatigue damage and the total creep damage. According to the method, the fatigue creep comprehensive life prediction method under the given actual road spectrum is constructed, the working life of the supercharger turbine can be predicted more accurately by comprehensively considering various influence factors of the turbine under the actual working condition, and therefore the performance and safety of the turbine are improved, and stable operation of the turbine is guaranteed.

A method for providing gearbox lubrication of a wind turbine during an off-grid state includes fluidly coupling an auxiliary lubrication system with a gearbox of the wind turbine. The off-grid state is characterized in that the wind turbine is mechanically and electrically installed at a wind farm but not yet connected to a grid. The method also includes determining a time-based control scheme for the auxiliary lubrication system to provide lubrication to the auxiliary lubrication system during the off-grid state. The time-based control scheme is defined a first time period in which the lubrication is provided to the gearbox via the auxiliary lubrication system during the off-grid state and a second time period in which the lubrication is not provided to the gearbox via the auxiliary lubrication system during the off-grid state. The first time period is less than the second time period. Further, the method includes implementing, via a controller, the control scheme for the auxiliary lubrication system to provide the lubrication to the gearbox of the wind turbine during the off-grid state.

A data monitoring system comprising a server communicatively coupled to a client device and a data module via a network. The server is configured to store a private key of a public-private key pair associated with the data module, receive a request from the client device for authenticated access to the data module, and generate an authentication key based at least on the private key and a time. The client device is configured to generate the request for authenticated access to the data module and transmit the request to the server. The data module is configured to store the private key of the public-private key pair associated with the data module, generate the authentication key based at least on the private key and the time, and grant access to the data module if the authentication key generated by the data module and the authentication key generated by the server match.

The invention discloses a machining tool management method and system based on a block chain, and the method comprises the following steps: S001, carrying out the precise locking of key time points before and after the sudden change of an order in a cutting process, and generating a time anchor point set; s002, on the basis of the time anchor point set, performing hourly decomposition on the multi-channel sensing signal, extracting temporary order components and conventional business components, and drawing a supply chain loop diagram in a business coupling direction; s003, identifying a high-risk business flow path based on the supply chain loop diagram, and generating a processing priority list at the same time; s004, dynamically adjusting a signal acquisition sequence and a data fusion sequence based on the processing priority list, and carrying out slow change budget distribution on an action threshold value of a service buffer gate; and S005, executing a discrete time slot and discrete period drift arrangement process based on the adaptive dynamic regulation seed, executing reversible time grid rearrangement and carrier gating rotation on each sensing signal channel, and completing stable suppression of temporary order fluctuation backflow.

The invention discloses a double-event triggering model prediction control method and system for a multi-working-condition industrial system, and the method comprises the steps: enabling a working condition change trigger to judge whether a new working condition occurs in the industrial system or not according to the data in an identification data buffer, and triggering the online updating of a prediction model if the new working condition occurs in the industrial system; the disturbance trigger judges whether a disturbance event triggering condition is achieved or not according to the data in the identification data buffer, and if the disturbance event triggering condition is achieved, optimization solution of the optimization controller is triggered; the optimization controller calculates a control sequence required by the industrial system in a next period of time based on the current prediction model; the control sequence buffer is used for storing the control sequence and the prediction output generated by the optimization controller. According to the method, the control precision can be improved, and meanwhile, the computing resource overhead is greatly saved.

A method and an apparatus for managing uplink transmission timing in conjunction with LTM operations is provided. The method comprises specific set of MAC CEs to update the uplink transmission timing of a specific TAG at a specific point of time. The terminal determines the specific TAG and the specific point of time based on the type of MAC CE containing the TAC and the contents contained within the MAC CE.

According to the rotor operation control method of the magnetic drive conveying system and the related equipment, the magnetic drive conveying system comprises a magnetic drive conveying track and a plurality of rotors, the rotors operate on the magnetic drive conveying track, and the method comprises the steps that the current load mass of each rotor is obtained, and the current operation distance between every two adjacent rotors is obtained; on the basis of the current load mass and the current operation spacing, the optimized operation speed of each rotor is calculated; calculating the control variation of each stator based on the optimized operation speed, and calculating the prediction position of each rotor at the prediction moment based on the control variation; based on the current load mass and the optimized operation speed, the operation safety distance between every two adjacent rotors is obtained through calculation; and when the predicted position represents that the predicted operation distance between every two adjacent rotors exceeds the operation safety distance, the stator is controlled based on the control variable quantity, so that operation control on the rotors is facilitated, and the safety of cooperative operation of the multiple rotors is remarkably improved.

The invention relates to a trajectory optimization method, a detector and electronic equipment, which are used for improving the trajectory accuracy of the detector in a set time period. The method comprises the following steps: taking the earliest time of a set time period as first time, taking an integral step length as a first integral step length, taking an initial motion state as a first motion state, and iteratively executing: determining a first duty ratio function value and a second duty ratio function value based on the first time, duty ratio reference time and the first integral step length; determining a second integral step length based on the first duty ratio function value, the second duty ratio function value and the threshold value; determining a second motion state of a second time based on the first motion state and a second integration step size, and taking the second motion state as a new first motion state, the second integration step size as a new first integration step size and the second time as a new first time until the second time reaches the latest time of the set time period; a trajectory is generated based on the initial motion state and the second motion state of each iterative process.

The invention discloses an electronic mechanical brake preset time control method based on disturbance estimation, which comprises the following steps that a dynamic model of an electronic mechanical brake is constructed, and the dynamic model of the electronic mechanical brake takes a braking force and a braking force change rate as state variables and takes q-axis current as control input; designing a predetermined time disturbance observer through the dynamical model of the electromechanical brake, and estimating lumped disturbance within a predetermined time based on the predetermined time disturbance observer; and designing a preset time sliding mode controller, compensating lumped disturbance of the system based on preset time, solving a control rate, and tracking the reference braking force. The transient and steady-state performance of braking force tracking control is improved.

The present invention provides a production scheduling method considering multi-cavity imbalance and machine failures, including the following steps: Step S11: Set the multi-cavity imbalance probability and machine failure rate for each machine, and set the corresponding upper and lower limits of the processing threshold; Step S12: Calculate the processing time based on the multi-cavity imbalance probability, machine failure rate, upper limit of the processing threshold, and lower limit of the processing threshold; Step S13: Set a dual-objective function of the maximum completion time of all workpieces and the total production energy consumption of all machines based on the processing time; Step S14: Use an optimization algorithm to solve and obtain a production scheduling plan. When dynamic disturbance events occur, different tasks are reasonably arranged to be processed on different machines, providing theoretical and technical support for enterprise processing.

A method for providing a schedule notification using an instant messaging application, the method being performed by one or more processors of a user terminal, includes obtaining a schedule message generated based on schedule information registered in a schedule application, determining a notification date and time based on the schedule message, and displaying the schedule message in a schedule notification area of the user terminal at a position in the instant message application corresponding to the determined notification date and time.

A server includes a circuitry, wherein the circuitry is configured to: obtain, at a first point of time during progress of a livestream, first time-series data representing content of the livestream recorded as the livestream progresses; generate summary information of the livestream as of the first point of time based on the first time-series data obtained; obtain, at a second point of time during progress of the livestream later than first point of time, second time-series data representing content of the livestream recorded as the livestream progresses; and generate summary information of the livestream as of the second point of time based on the second time-series data obtained.

The present disclosure provides a system and a computer-implemented method for monitoring and / or controlling a product carbon footprint, PCF, of a product produced in a production process. The method comprises receiving PCF-related data for a first and / or a second point in time; calculating a first PCF of the product at the first point in time and a second PCF of the product at the second point in time based on the PCF-related data; calculating at least a first PCF of an intermediate of the product at a first point in time and a second PCF of the intermediate at a second point in time based on the PCF-related data; identifying at least one influencing factor within the production process for a change in value between the first and second PCF of the product based on the first and second PCF of the intermediate; and outputting the identified at least one influencing factor.

This application relates to apparatus and methods for generating and implementing a machine learning model in electronic delivery systems to determine delivery routes and times. In some examples, a computing device generates a machine learning model comprising a plurality of indexed binary trees. Each indexed binary tree determines either a first value, or a second value, based on comparing an input to a condition value. The machine learning model can generate prediction values based on the determined values of all indexed binary trees. The machine learning model is trained with historical data. Once trained, the machine learning model's performance is evaluated. Based on the evaluation, the machine learning model may be further refined. Once the machine learning model's performance satisfies requirements, the computing device employs the machine learning model to determine vehicle delivery routes and estimated delivery times.

The invention relates to the technical field of equipment fault diagnosis, and particularly discloses a fault diagnosis method and system for water station equipment, and the method comprises an information collection module which collects the operation data information of all equipment of a water station in real time; the data processing module is used for receiving the operation data information of each device and preprocessing the operation data information; the fault diagnosis module is used for comparing the operation data information of each device with the normal operation parameters to judge whether a fault exists or not, and predicting the fault occurrence rate of the corresponding device within a period of time according to the previous data; and the display control module is used for automatically displaying a fault judgment result of the fault diagnosis module when a fault occurs and giving a possible reason. According to the invention, the real-time operation parameters of each device of the water station are collected, the abnormal state of the device is found in time, the fault is quickly responded, the influence of the fault on the operation of the water station is reduced, possible reasons and the fault occurrence rate are given, workers are reminded to overhaul and maintain in time, the overhaul efficiency is improved, and the fault probability is reduced.

A counterfeit item detection system detects counterfeit items during an item listing processes provided by an online marketplace. The system enhances the ability of the online marketplace to identify and reject potential counterfeit items. The system comprises a trained counterfeit item detection model that is configured to receive an image and identify whether the image includes a counterfeit item. The model is trained using a data set of training images. An image of the data set is taken from a video related to the time based on identifying that the context of text associated with the video relates to counterfeit items. The text can be determined from the video's audio, and the image is obtained at a time in the video where the text corresponds to a counterfeit item context.

The invention discloses a driving control method of an interleaving parallel flyback micro inverter. The driving control method comprises the following steps: comparing the total output power of the interleaved parallel flyback micro inverter with the maximum output power of a single branch; when the total output power of the interleaved parallel flyback micro inverter is smaller than the maximum output power of a single branch, determining a time point corresponding to the maximum value according to the peak current reference value, and controlling the first transformer and the second transformer to work alternately based on the time point; and when the total output power of the interleaving flyback micro inverter is greater than or equal to the maximum output power of the single branch, determining a time interval corresponding to the condition that the total output power is greater than or equal to the maximum output power of the single branch, and controlling the first transformer and the second transformer to work at the same time in the time interval, and alternately working outside the time interval. According to the technical scheme, the aging difference of branch devices can be effectively reduced, and the situation that branch heat accumulation is serious is avoided.

An example operation may include one or more of ingesting data from a plurality of systems, dividing the data into a plurality of bins based on binning configuration settings, identifying a bin of data among the plurality of bins which contains an anomaly at a point in time based on thresholds for the plurality of bins, identifying a different bin of data among the plurality of bins which does not contain the anomaly at the point in time based on the thresholds for the plurality of bins, generating a heat map comprising a plurality of display elements corresponding to the plurality of bins including a display element corresponding to the bin of data with the anomaly with a different visual appearance than a display element corresponding to the different bin which does not contain the anomaly, and rendering the heat map via a GUI.